Within-host selection is limited by an effective population of Streptococcus pneumoniae during nasopharyngeal colonization

Long-term evolution of Streptococcus mitis and Streptococcus pneumoniae leads to higher genetic diversity within rather than between human populations

Evaluation of the apportionment of genetic diversity of human bacterial commensals within and between human populations is an important step in the characterization of their evolutionary potential. Recent studies showed a correlation between the genomic diversity of human commensal strains and that of their host, but the strength of this correlation and of the geographic structure among human populations is a matter of debate. Here, we studied the genomic diversity and evolution of the phylogenetically related oro-nasopharyngeal healthy-carriage Streptococcus mitis and Streptococcus pneumoniae, whose lifestyles range from stricter commensalism to high pathogenic potential. A total of 119 S. mitis genomes showed higher within- and among-host variation than 810 S. pneumoniae genomes in European, East Asian and African populations. Summary statistics of the site-frequency spectrum for synonymous and non-synonymous variation and ABC modelling showed this difference to be due to higher ancestral bacterial population effective size (Ne) in S. mitis, whose genomic variation has been maintained close to mutation-drift equilibrium across (at least many) generations, whereas S. pneumoniae has been expanding from a smaller ancestral bacterial population. Strikingly, both species show limited differentiation among human populations. As genetic differentiation is inversely proportional to the product of effective population size and migration rate (Nem), we argue that large Ne have led to similar differentiation patterns, even if m is very low for S. mitis. We conclude that more diversity within than among human populations and limited population differentiation must be common features of the human microbiome due to large Ne.

How colonization bottlenecks, tissue niches, and transmission strategies shape protozoan infections

Protozoan pathogens such as Plasmodium spp., Leishmania spp., Toxoplasma gondii, and Trypanosoma spp. are often associated with high-mortality, acute and chronic diseases of global health concern. For transmission and immune evasion, protozoans have evolved diverse strategies to interact with a range of host tissue environments. These interactions are linked to disease pathology, yet our understanding of the association between parasite colonization and host homeostatic disruption is limited. Recently developed techniques for cellular barcoding have the potential to uncover the biology regulating parasite transmission, dissemination, and the stability of infection. Understanding bottlenecks to infection and the in vivo tissue niches that facilitate chronic infection and spread has the potential to reveal new aspects of parasite biology.

Fitness advantage of Bacteroides thetaiotaomicron capsular polysaccharide in the mouse gut depends on the resident microbiota

Many microbiota-based therapeutics rely on our ability to introduce a microbe of choice into an already-colonized intestine. In this study, we used genetically barcoded Bacteroides thetaiotaomicron (B. theta) strains to quantify population bottlenecks experienced by a B. theta population during colonization of the mouse gut. As expected, this reveals an inverse relationship between microbiota complexity and the probability that an individual wildtype B. theta clone will colonize the gut. The polysaccharide capsule of B. theta is important for resistance against attacks from other bacteria, phage, and the host immune system, and correspondingly acapsular B. theta loses in competitive colonization against the wildtype strain. Surprisingly, the acapsular strain did not show a colonization defect in mice with a low-complexity microbiota, as we found that acapsular strains have an indistinguishable colonization probability to the wildtype strain on single-strain colonization. This discrepancy could be resolved by tracking in vivo growth dynamics of both strains: acapsular B.theta shows a longer lag phase in the gut lumen as well as a slightly slower net growth rate. Therefore, as long as there is no niche competitor for the acapsular strain, this has only a small influence on colonization probability. However, the presence of a strong niche competitor (i.e., wildtype B. theta, SPF microbiota) rapidly excludes the acapsular strain during competitive colonization. Correspondingly, the acapsular strain shows a similarly low colonization probability in the context of a co-colonization with the wildtype strain or a complete microbiota. In summary, neutral tagging and detailed analysis of bacterial growth kinetics can therefore quantify the mechanisms of colonization resistance in differently-colonized animals.

BlpC-mediated selfish program leads to rapid loss of Streptococcus pneumoniae clonal diversity during infection

Successful colonization of a host requires bacterial adaptation through genetic and population changes that are incompletely defined. Using chromosomal barcoding and high-throughput sequencing, we investigate the population dynamics of Streptococcus pneumoniae during infant mouse colonization. Within 1 day post inoculation, diversity was reduced >35-fold with expansion of a single clonal lineage. This loss of diversity was not due to immune factors, microbiota, or exclusive genetic drift. Rather, bacteriocins induced by the BlpC-quorum sensing pheromone resulted in predation of kin cells. In this intra-strain competition, the subpopulation reaching a quorum likely eliminates others that have yet to activate the blp locus. Additionally, this reduced diversity restricts the number of unique clones that establish colonization during transmission between hosts. Genetic variation in the blp locus was also associated with altered transmissibility in a human population, further underscoring the importance of BlpC in clonal selection and its role as a selfish element.

Rapid expansion and extinction of antibiotic resistance mutations during treatment of acute bacterial respiratory infections

Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. The effects of such rapid antibiotic switching on the evolution of antibiotic resistance in individual patients are poorly understood. Here we find that low-frequency antibiotic resistance mutations emerge, contract, and even go to extinction within days of changes in therapy. We analyzed Pseudomonas aeruginosa populations in sputum samples collected serially from 7 mechanically ventilated patients at the onset of respiratory infection. Combining short- and long-read sequencing and resistance phenotyping of 420 isolates revealed that while new infections are near-clonal, reflecting a recent colonization bottleneck, resistance mutations could emerge at low frequencies within days of therapy. We then measured the in vivo frequencies of select resistance mutations in intact sputum samples with resistance-targeted deep amplicon sequencing (RETRA-Seq), which revealed that rare resistance mutations not detected by clinically used culture-based methods can increase by nearly 40-fold over 5–12 days in response to antibiotic changes. Conversely, mutations conferring resistance to antibiotics not administered diminish and even go to extinction. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patient-specific antibiotic cycling strategies informed by deep genomic surveillance.

It remains unclear how rapid antibiotic switching affects the evolution of antibiotic resistance in individual patients. Here, Chung et al. combine short- and long-read sequencing and resistance phenotyping of 420 serial isolates of Pseudomonas aeruginosa collected from the onset of respiratory infection, and show that rare resistance mutations can increase by nearly 40-fold over 5–12 days in response to antibiotic changes, while mutations conferring resistance to antibiotics not administered diminish and even go to extinction.

Pneumococcal capsule blocks protection by immunization with conserved surface proteins

Vaccines targeting Streptococcus pneumoniae (Spn) are limited by dependence on capsular polysaccharide and its serotype diversity. More broadly-based approaches using common protein antigens have not resulted in a licensed vaccine. Herein, we used an unbiased, genome-wide approach to find novel vaccine antigens to disrupt carriage modeled in mice. A Tn-Seq screen identified 198 genes required for colonization of which 16 are known to express conserved, immunogenic surface proteins. After testing defined mutants for impaired colonization of infant and adult mice, 5 validated candidates (StkP, PenA/Pbp2a, PgdA, HtrA, and LytD/Pce/CbpE) were used as immunogens. Despite induction of antibody recognizing the Spn cell surface, there was no protection against Spn colonization. There was, however, protection against an unencapsulated Spn mutant. This result correlated with increased antibody binding to the bacterial surface in the absence of capsule. Our findings demonstrate how the pneumococcal capsule interferes with mucosal protection by antibody to common protein targets.

Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR

Pathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering these dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult because measuring bacterial burden alone is insufficient to observe these patterns. Introduction of allelic diversity into otherwise identical bacteria using DNA barcodes enables sequencing-based measurements of these parameters, in a method known as STAMP (Sequence Tag-based Analysis of Microbial Populations). However, bacteria often undergo unequal expansion within host organs, resulting in marked differences in the frequencies of barcodes in input and output libraries. Here, we show that these differences confound STAMP-based analyses of founding population sizes and dissemination patterns. We present STAMPR, a successor to STAMP, which accounts for such population expansions. Using data from systemic infection of barcoded extraintestinal pathogenic E. coli, we show that this new framework, along with the metrics it yields, enhances the fidelity of measurements of bottlenecks and dissemination patterns. STAMPR was also validated on an independent barcoded Pseudomonas aeruginosa data set, uncovering new patterns of dissemination within the data. This framework (available at https://github.com/hullahalli/stampr_rtisan), when coupled with barcoded data sets, enables a more complete assessment of within-host bacterial population dynamics. IMPORTANCE Barcoded bacteria are often employed to monitor pathogen population dynamics during infection. The accuracy of these measurements is diminished by unequal bacterial expansion rates. Here, we develop computational tools to circumvent this limitation and establish additional metrics that collectively enhance the fidelity of measuring within-host pathogen founding population sizes and dissemination patterns. These new tools will benefit future studies of the dynamics of pathogens and symbionts within their respective hosts and may have additional barcode-based applications beyond host-microbe interactions.

Exploration of Bacterial Bottlenecks and Streptococcus pneumoniae Pathogenesis by CRISPRi-Seq

Streptococcus pneumoniae is an opportunistic human pathogen that causes invasive diseases, including pneumonia, with greater health risks upon influenza A virus (IAV) co-infection. To facilitate pathogenesis studies in vivo, we developed an inducible CRISPR interference system that enables genome-wide fitness testing in one sequencing step (CRISPRi-seq). We applied CRISPRi-seq to assess bottlenecks and identify pneumococcal genes important in a murine pneumonia model. A critical bottleneck occurs at 48 h with few bacteria causing systemic infection. This bottleneck is not present during IAV superinfection, facilitating identification of pneumococcal pathogenesis-related genes. Top in vivo essential genes included purA, encoding adenylsuccinate synthetase, and the cps operon required for capsule production. Surprisingly, CRISPRi-seq indicated no fitness-related role for pneumolysin during superinfection. Interestingly, although metK (encoding S-adenosylmethionine synthetase) was essential in vitro, it was dispensable in vivo. This highlights advantages of CRISPRi-seq over transposon-based genetic screens, as all genes, including essential genes, can be tested for pathogenesis potential.

Elucidating host-microbe interactions in vivo by studying population dynamics using neutral genetic tags

Host–microbe interactions are highly dynamic in space and time, in particular in the case of infections. Pathogen population sizes, microbial phenotypes and the nature of the host responses often change dramatically over time. These features pose particular challenges when deciphering the underlying mechanisms of these interactions experimentally, as traditional microbiological and immunological methods mostly provide snapshots of population sizes or sparse time series. Recent approaches – combining experiments using neutral genetic tags with stochastic population dynamic models – allow more precise quantification of biologically relevant parameters that govern the interaction between microbe and host cell populations. This is accomplished by exploiting the patterns of change of tag composition in the microbe or host cell population under study. These models can be used to predict the effects of immunodeficiencies or therapies (e.g. antibiotic treatment) on populations and thereby generate hypotheses and refine experimental designs. In this review, we present tools to study population dynamics in vivo using genetic tags, explain examples for their implementation and briefly discuss future applications.

Within-host microevolution of Streptococcus pneumoniae is rapid and adaptive during natural colonisation

Genomic evolution, transmission and pathogenesis of Streptococcus pneumoniae, an opportunistic human-adapted pathogen, is driven principally by nasopharyngeal carriage. However, little is known about genomic changes during natural colonisation. Here, we use whole-genome sequencing to investigate within-host microevolution of naturally carried pneumococci in ninety-eight infants intensively sampled sequentially from birth until twelve months in a high-carriage African setting. We show that neutral evolution and nucleotide substitution rates up to forty-fold faster than observed over longer timescales in S. pneumoniae and other bacteria drives high within-host pneumococcal genetic diversity. Highly divergent co-existing strain variants emerge during colonisation episodes through real-time intra-host homologous recombination while the rest are co-transmitted or acquired independently during multiple colonisation episodes. Genic and intergenic parallel evolution occur particularly in antibiotic resistance, immune evasion and epithelial adhesion genes. Our findings suggest that within-host microevolution is rapid and adaptive during natural colonisation.

Models of immune selection for multi-locus antigenic diversity of pathogens

It is well accepted that pathogens can evade recognition and elimination by the host immune system by varying their antigenic targets. Thus, it has become a truism that host immunity is a major driver and determinant of the antigenic diversity of pathogens. However, it remains puzzling how host immunity selects for antigenic diversity at the level of the pathogen population, given that hosts have acquired immune responses to multiple antigens of most pathogens - sometimes through multiple effectors of both humoral and cellular immunity. In this Opinion article, we address this puzzle and the related question of why pathogens often have diversity at multiple antigenic loci. Here, we describe five hypotheses to explain the polymorphism of multiple antigens in a single pathogen species and highlight research relevant to our current models of thinking about multi-locus antigenic diversity.

Microevolution of Neisseria lactamica during nasopharyngeal colonisation induced by controlled human infection

Neisseria lactamica is a harmless coloniser of the infant respiratory tract, and has a mutually-excluding relationship with the pathogen Neisseria meningitidis. Here we report controlled human infection with genomically-defined N. lactamica and subsequent bacterial microevolution during 26 weeks of colonisation. We find that most mutations that occur during nasopharyngeal carriage are transient indels within repetitive tracts of putative phase-variable loci associated with host-microbe interactions (pgl and lgt) and iron acquisition (fetA promotor and hpuA). Recurrent polymorphisms occurred in genes associated with energy metabolism (nuoN, rssA) and the CRISPR-associated cas1. A gene encoding a large hypothetical protein was often mutated in 27% of the subjects. In volunteers who were naturally co-colonised with meningococci, recombination altered allelic identity in N. lactamica to resemble meningococcal alleles, including loci associated with metabolism, outer membrane proteins and immune response activators. Our results suggest that phase variable genes are often mutated during carriage-associated microevolution.

Frequency-dependent selection in vaccine-associated pneumococcal population dynamics

Many bacterial species are composed of multiple lineages distinguished by extensive variation in gene content. These often cocirculate in the same habitat, but the evolutionary and ecological processes that shape these complex populations are poorly understood. Addressing these questions is particularly important for Streptococcus pneumoniae, a nasopharyngeal commensal and respiratory pathogen, because the changes in population structure associated with the recent introduction of partial-coverage vaccines have substantially reduced pneumococcal disease. Here we show that pneumococcal lineages from multiple populations each have a distinct combination of intermediate-frequency genes. Functional analysis suggested that these loci may be subject to negative frequency-dependent selection (NFDS) through interactions with other bacteria, hosts or mobile elements. Correspondingly, these genes had similar frequencies in four populations with dissimilar lineage compositions. These frequencies were maintained following substantial alterations in lineage prevalences once vaccination programmes began. Fitting a multilocus NFDS model of post-vaccine population dynamics to three genomic datasets using Approximate Bayesian Computation generated reproducible estimates of the influence of NFDS on pneumococcal evolution, the strength of which varied between loci. Simulations replicated the stable frequency of lineages unperturbed by vaccination, patterns of serotype switching and clonal replacement. This framework highlights how bacterial ecology affects the impact of clinical interventions.

An efficient moments-based inference method for within-host bacterial infection dynamics

Over the last ten years, isogenic tagging (IT) has revolutionised the study of bacterial infection dynamics in laboratory animal models. However, quantitative analysis of IT data has been hindered by the piecemeal development of relevant statistical models. The most promising approach relies on stochastic Markovian models of bacterial population dynamics within and among organs. Here we present an efficient numerical method to fit such stochastic dynamic models to in vivo experimental IT data. A common approach to statistical inference with stochastic dynamic models relies on producing large numbers of simulations, but this remains a slow and inefficient method for all but simple problems, especially when tracking bacteria in multiple locations simultaneously. Instead, we derive and solve the systems of ordinary differential equations for the two lower-order moments of the stochastic variables (mean, variance and covariance). For any given model structure, and assuming linear dynamic rates, we demonstrate how the model parameters can be efficiently and accurately estimated by divergence minimisation. We then apply our method to an experimental dataset and compare the estimates and goodness-of-fit to those obtained by maximum likelihood estimation. While both sets of parameter estimates had overlapping confidence regions, the new method produced lower values for the division and death rates of bacteria: these improved the goodness-of-fit at the second time point at the expense of that of the first time point. This flexible framework can easily be applied to a range of experimental systems. Its computational efficiency paves the way for model comparison and optimal experimental design.

Evolutionary Constraints Shaping Streptococcus pyogenes-Host Interactions

Research on the Gram-positive human-restricted pathogen Streptococcus pyogenes (Group A Streptococcus, GAS) has long focused on invasive illness, the most severe manifestations of GAS infection. Recent advances in descriptions of molecular mechanisms of GAS virulence, coupled with massive sequencing efforts to isolate genomes, have allowed the field to better understand the molecular and evolutionary changes leading to pandemic strains. These findings suggest that it is necessary to rethink the dogma involving GAS pathogenesis, and that the most productive avenues for research going forward may be investigations into GAS in its 'normal' habitat, the nasopharynx, and its ability to either live with its host in an asymptomatic lifestyle or as an agent of superficial infections. This review will consider these advances, focusing on the natural history of GAS, the evolution of pandemic strains, and novel roles for several key virulence factors that may allow the field to better understand their physiological role.

Single Cell Bottlenecks in the Pathogenesis of Streptococcus pneumoniae

Herein, we studied a virulent isolate of the leading bacterial pathogen Streptococcus pneumoniae in an infant mouse model of colonization, disease and transmission, both with and without influenza A (IAV) co-infection. To identify vulnerable points in the multiple steps involved in pneumococcal pathogenesis, this model was utilized for a comprehensive analysis of population bottlenecks. Our findings reveal that in the setting of IAV co-infection the organism must pass through single cell bottlenecks during bloodstream invasion from the nasopharynx within the host and in transmission between hosts. Passage through these bottlenecks was not associated with genetic adaptation by the pathogen. The bottleneck in transmission occurred between bacterial exit from one host and establishment in another explaining why the number of shed organisms in secretions is critical to overcoming it. These observations demonstrate how viral infection, and TLR-dependent innate immune responses it stimulates and that are required to control it, drive bacterial contagion.

Many discrete steps are involved in the progression of infectious diseases. Bottlenecks represent key points where the population size/genetic diversity is at a minimum and the pathogen is most vulnerable to intervention strategies. Our study used an infant mouse model for a comprehensive analysis of bottlenecks in infection by the major pathogen Streptococcus pneumoniae. In our model, we also considered influenza A virus, a clinically important and common co-infection. The main findings reveal i) a single cell bottleneck during host-to-host transmission and ii) the bottleneck in transmission occurs during events between bacterial exit from one host and establishment in another host. We manipulated innate immune responses involved in viral control and inflammation to show that viral co-infection allows the bottleneck in transmission to be overcome by increasing bacterial exit. Finally, we demonstrate that a specific host response stimulated by influenza A is sufficient to recapitulate effects of viral co-infection. Thus, our study identifies key vulnerable stages during S. pneumoniae infection and provides mechanistic understanding for how viral infection promotes bacterial contagion.

Horizontal DNA Transfer Mechanisms of Bacteria as Weapons of Intragenomic Conflict

Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell-cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing "arms race." Reduced rates of transformation have also been observed in cells infected by MGEs that reduce the concentration of extracellular DNA through secretion of DNases. Simulations predicted that either mechanism of limiting transformation would benefit individual MGEs, but also that this tactic's effectiveness was limited by competition with other MGEs coinfecting the same cell. A further observed behaviour we hypothesised to reduce elimination by transformation was MGE activation when cells become competent. Our model predicted that this response was effective at counteracting transformation independently of competing MGEs. Therefore, this framework is able to explain both common properties of MGEs, and the seemingly paradoxical bacterial behaviours of transformation and cell-cell killing within clonally related populations, as the consequences of intragenomic conflict between self-replicating chromosomes and parasitic MGEs. The antagonistic nature of the different mechanisms of HDT over short timescales means their contribution to bacterial evolution is likely to be substantially greater than previously appreciated.

Effect of Serotype on Pneumococcal Competition in a Mouse Colonization Model

Competitive interactions between Streptococcus pneumoniae strains during host colonization could influence the serotype distribution in nasopharyngeal carriage and pneumococcal disease. We evaluated the competitive fitness of strains of serotypes 6B, 14, 19A, 19F, 23F, and 35B in a mouse model of multiserotype carriage. Isogenic variants were constructed using clinical strains as the capsule gene donors. Animals were intranasally inoculated with a mixture of up to six pneumococcal strains of different serotypes, with separate experiments involving either clinical isolates or isogenic capsule-switch variants of clinical strain TIGR4. Upper-respiratory-tract samples were repeatedly collected from animals in order to monitor changes in the serotype ratios using quantitative PCR. A reproducible hierarchy of capsular types developed in the airways of mice inoculated with multiple strains. Serotype ranks in this hierarchy were similar among pneumococcal strains of different genetic backgrounds in different strains of mice and were not altered when tested under a range of host conditions. This rank correlated with the measure of the metabolic cost of capsule synthesis and in vitro measure of pneumococcal cell surface charge, both parameters considered to be predictors of serotype-specific fitness in carriage. This study demonstrates the presence of a robust competitive hierarchy of pneumococcal serotypes in vivo that is driven mainly, but not exclusively, by the capsule itself.

Streptococcus pneumoniae (pneumococcus) is the leading cause of death due to respiratory bacterial infections but also a commensal frequently carried in upper airways. Available vaccines induce immune responses against polysaccharides coating pneumococcal cells, but with over 90 different capsular types (serotypes) identified, they can only target strains of the selected few serotypes most prevalent in disease. Vaccines not only protect vaccinated individuals against disease but also protect by reducing carriage of vaccine-targeted strains to induce herd effects across whole populations. Unfortunately, reduction in the circulation of vaccine-type strains is offset by increase in carriage and disease from nonvaccine strains, indicating the importance of competitive interactions between pneumococci in shaping the population structure of this pathogen. Here, we showed that the competitive ability of pneumococcal strains to colonize the host strongly depends on the type of capsular polysaccharide expressed by pneumococci and only to a lesser degree on strain or host genetic backgrounds or on variation in host immune responses.

Identification of pneumococcal colonization determinants in the stringent response pathway facilitated by genomic diversity

BACKGROUND

Understanding genetic determinants of a microbial phenotype generally involves creating and comparing isogenic strains differing at the locus of interest, but the naturally existing genomic and phenotypic diversity of microbial populations has rarely been exploited. Here we report use of a diverse collection of 616 carriage isolates of Streptococcus pneumoniae and their genome sequences to help identify a novel determinant of pneumococcal colonization.

RESULTS

A spontaneously arising laboratory variant (SpnYL101) of a capsule-switched TIGR4 strain (TIGR4:19F) showed reduced ability to establish mouse nasal colonization and lower resistance to non-opsonic neutrophil-mediated killing in vitro, a phenotype correlated with in vivo success. Whole genome sequencing revealed 5 single nucleotide polymorphisms (SNPs) affecting 4 genes in SpnYL101 relative to its ancestor. To evaluate the effect of variation in each gene, we performed an in silico screen of 616 previously published genome sequences to identify pairs of closely-related, serotype-matched isolates that differ at the gene of interest, and compared their resistance to neutrophil-killing. This method allowed rapid examination of multiple candidate genes and found phenotypic differences apparently associated with variation in SP_1645, a RelA/ SpoT homolog (RSH) involved in the stringent response. To establish causality, the alleles corresponding to SP_1645 were switched between the TIGR4:19F and SpnYL101. The wild-type SP_1645 conferred higher resistance to neutrophil-killing and competitiveness in mouse colonization. Using a similar strategy, variation in another RSH gene (TIGR4 locus tag SP_1097) was found to alter resistance to neutrophil-killing.

CONCLUSIONS

These results indicate that analysis of naturally existing genomic diversity complements traditional genetics approaches to accelerate genotype-phenotype analysis.

Sequence tag-based analysis of microbial population dynamics

We describe sequence tag-based analysis of microbial populations (STAMP) for characterization of pathogen population dynamics during infection. STAMP analyzes the frequency changes of genetically 'barcoded' organisms to quantify population bottlenecks and infer the founding population size. Analyses of intraintestinal Vibrio cholerae revealed infection-stage and region-specific host barriers to infection and showed unexpected V. cholerae migration counter to intestinal flow. STAMP provides a robust, widely applicable analytical framework for high-confidence characterization of in vivo microbial dissemination.

Within-host bacterial diversity hinders accurate reconstruction of transmission networks from genomic distance data

The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmission routes using genomic data; however, these have typically relied upon restrictive assumptions, such as a shared topology of the phylogenetic tree and a lack of within-host diversity. In this study, we investigated the potential for bacterial genomic data to inform transmission network reconstruction. We used simulation models to investigate the origins, persistence and onward transmission of genetic diversity, and examined the impact of such diversity on our estimation of the epidemiological relationship between carriers. We used a flexible distance-based metric to provide a weighted transmission network, and used receiver-operating characteristic (ROC) curves and network entropy to assess the accuracy and uncertainty of the inferred structure. Our results suggest that sequencing a single isolate from each case is inadequate in the presence of within-host diversity, and is likely to result in misleading interpretations of transmission dynamics – under many plausible conditions, this may be little better than selecting transmission links at random. Sampling more frequently improves accuracy, but much uncertainty remains, even if all genotypes are observed. While it is possible to discriminate between clusters of carriers, individual transmission routes cannot be resolved by sequence data alone. Our study demonstrates that bacterial genomic distance data alone provide only limited information on person-to-person transmission dynamics.

With the advent of affordable large-scale genome sequencing for bacterial pathogens, there is much interest in using such data to identify who infected whom in a disease outbreak. Many methods exist to reconstruct the phylogeny of sampled bacteria, but the resulting tree does not necessarily share the same structure as the transmission tree linking infected persons. We explored the potential of sampled genomic data to inform the transmission tree, measuring the accuracy and precision of estimated networks based on simulated data. We demonstrated that failing to account for within-host diversity can lead to poor network reconstructions - even with repeated sampling of each carrier, there is still much uncertainty in the estimated structure. While it may be possible to identify clusters of potential sources, identifying individual transmission links is not possible using bacterial sequence data alone. This work highlights potential limitations of genomic data to investigate transmission dynamics, lending support to methods unifying all available data sources.