Niche and neutral effects of acquired immunity permit coexistence of pneumococcal serotypes

Convergent impact of vaccination and antibiotic pressures on pneumococcal populations

Streptococcus pneumoniae is a remarkably adaptable and successful human pathogen, playing dual roles of both asymptomatic carriage in the nasopharynx and invasive disease including pneumonia, bacteremia, and meningitis. Efficacious vaccines and effective antibiotic therapies are critical to mitigating morbidity and mortality. However, clinical interventions can be rapidly circumvented by the pneumococcus by its inherent proclivity for genetic exchange. This leads to an underappreciated interplay between vaccine and antibiotic pressures on pneumococcal populations. Circulating populations have undergone dramatic shifts due to the introduction of capsule-based vaccines of increasing valency imparting strong selective pressures. These alterations in population structure have concurrent consequences on the frequency of antibiotic resistance profiles in the population. This review will discuss the interactions of these two selective forces. Understanding and forecasting the drivers of antibiotic resistance and capsule switching are of critical importance for public health, particularly for such a genetically promiscuous pathogen as S. pneumoniae.

Genomic and panproteomic analysis of the development of infant immune responses to antigenically-diverse pneumococci

Streptococcus pneumoniae (pneumococcus) is a nasopharyngeal commensal and respiratory pathogen. This study characterises the immunoglobulin G (IgG) repertoire recognising pneumococci from birth to 24 months old (mo) in a prospectively-sampled cohort of 63 children using a panproteome array. IgG levels are highest at birth, due to transplacental transmission of maternal antibodies. The subsequent emergence of responses to individual antigens exhibit distinct kinetics across the cohort. Stable differences in the strength of individuals' responses, correlating with maternal IgG concentrations, are established by 6 mo. By 12 mo, children develop unique antibody profiles that are boosted by re-exposure. However, some proteins only stimulate substantial responses in adults. Integrating genomic data on nasopharyngeal colonisation demonstrates rare pneumococcal antigens can elicit strong IgG levels post-exposure. Quantifying such responses to the diverse core loci (DCL) proteins is complicated by cross-immunity between variants. In particular, the conserved N terminus of DCL protein zinc metalloprotease B provokes the strongest early IgG responses. DCL proteins' ability to inhibit mucosal immunity likely explains continued pneumococcal carriage despite hosts' polyvalent antibody repertoire. Yet higher IgG levels are associated with reduced incidence, and severity, of pneumonia, demonstrating the importance of the heterogeneity in response strength and kinetics across antigens and individuals.

Impact of vaccines on Staphylococcus aureus colonization: A systematic review and meta-analysis

BACKGROUND

Concerns regarding vaccine effects on microbial ecology have led to interest in the non-targeted effects of vaccinations.

OBJECTIVES

To systematically review the literature related to the impact of vaccines on S. aureus carriage.

METHODS

We conducted a systematic search of MEDLINE, Scopus and clinical trials.gov for studies that assessed vaccine effects on S. aureus carriage in children and adults using predefined inclusion and exclusion criteria. Generic inverse variance meta-analysis was done using random-effects models.

RESULTS

Of 1,686 studies screened, 34 were eligible for inclusion, of which 22 were observational and 12 randomized controlled studies (RCTs). 88.2% (30/34) provided data on pneumococcal conjugate vaccines (PCV), 23.5% on influenza vaccines (8/34), 6% on other vaccines (2/34) and 20.6% on more than one vaccine (7/34). Most studies tested nasopharyngeal specimens (82.3%, 28/34). Among children aged more than 18-24 months, evidence suggested no effect of PCV on S. aureus colonization [2 RCTs, pooled OR 1.09 (95% CI 0.94-1.25), p 0.25; 7 observational studies, pooled OR: 1.02 (95% CI 0.83-1.25), p 0.86]. A transient increase in S. aureus carriage in PCV-vaccinated infants 9-15 months was shown [2 RCTs, pooled OR 1.11 (95% CI 1.00-1.23), p 0.06; 4 observational studies, pooled OR 1.64 (95% CI 1.00-2.68), p 0.05]. A reduction in S. aureus carriage was observed after influenza vaccination [4 observational studies; OR 0.85 (95% CI 0.78-0.94), p 0.0001]. Based on the Grading of Recommendations Assessment, Development and Evaluation, the quality of evidence was considered low for randomized and very low for non-randomized trials.

CONCLUSION

Evidence did not suggest long-term effects of pneumococcal vaccinations on S. aureus nasopharyngeal carriage in children, however transient niche changes may occur in infants. Influenza vaccination was related to decreased rates of S. aureus carriage. Data regarding other vaccines is scarce. Further research and ongoing surveillance are needed to monitor colonization changes.

Quasi-neutral dynamics in a coinfection system with N strains and asymmetries along multiple traits

Understanding the interplay of different traits in a co-infection system with multiple strains has many applications in ecology and epidemiology. Because of high dimensionality and complex feedback between traits manifested in infection and co-infection, the study of such systems remains a challenge. In the case where strains are similar (quasi-neutrality assumption), we can model trait variation as perturbations in parameters, which simplifies analysis. Here, we apply singular perturbation theory to many strain parameters simultaneously and advance analytically to obtain their explicit collective dynamics. We consider and study such a quasi-neutral model of susceptible-infected-susceptible (SIS) dynamics among N strains, which vary in 5 fitness dimensions: transmissibility, clearance rate of single- and co-infection, transmission probability from mixed coinfection, and co-colonization vulnerability factors encompassing cooperation and competition. This quasi-neutral system is analyzed with a singular perturbation method through an appropriate slow-fast decomposition. The fast dynamics correspond to the embedded neutral system, while the slow dynamics are governed by an N-dimensional replicator equation, describing the time evolution of strain frequencies. The coefficients of this replicator system are pairwise invasion fitnesses between strains, which, in our model, are an explicit weighted sum of pairwise asymmetries along all trait dimensions. Remarkably these weights depend only on the parameters of the neutral system. Such model reduction highlights the centrality of the neutral system for dynamics at the edge of neutrality and exposes critical features for the maintenance of diversity.

Reconstructing multi-strain pathogen interactions from cross-sectional survey data via statistical network inference

Infectious diseases often involve multiple pathogen species or multiple strains of the same pathogen. As such, knowledge of how different pathogens interact is key to understand and predict the outcome of interventions targeting only a subset of species or strains involved in disease. Population-level data may be useful to infer pathogen strain interactions, but most previously used inference methods only consider uniform interactions between all strains or focus on marginal pairwise interactions. As such, these methods are prone to bias induced by indirect interactions through other strains. Here, we evaluated statistical network inference for reconstructing heterogeneous interactions from cross-sectional surveys detecting joint presence/absence patterns of pathogen strains within hosts. We applied various network models to simulated survey data, representing endemic infection states of multiple pathogen strains with potential interactions in acquisition or clearance of infection. Satisfactory performance was demonstrated by the estimators converging to the true interactions. Accurate reconstruction of interaction networks was achieved by regularization or penalization for sample size. Although performance deteriorated in the presence of host heterogeneity, this was overcome by correcting for individual-level risk factors. Our work demonstrates how statistical network inference could prove useful for detecting multi-strain pathogen interactions and may have applications beyond epidemiology.

Increased vaccine sensitivity of an emerging SARS-CoV-2 variant

Host immune responses are a key source of selective pressure driving pathogen evolution. Emergence of many SARS-CoV-2 lineages has been associated with enhancements in their ability to evade population immunity resulting from both vaccination and infection. Here we show diverging trends of escape from vaccine-derived and infection-derived immunity for the emerging XBB/XBB.1.5 Omicron lineage. Among 31,739 patients tested in ambulatory settings in Southern California from December, 2022 to February, 2023, adjusted odds of prior receipt of 2, 3, 4, and ≥5 COVID-19 vaccine doses were 10% (95% confidence interval: 1-18%), 11% (3-19%), 13% (3-21%), and 25% (15-34%) lower, respectively, among cases infected with XBB/XBB.1.5 than among cases infected with other co-circulating lineages. Similarly, prior vaccination was associated with greater point estimates of protection against progression to hospitalization among cases with XBB/XBB.1.5 than among non-XBB/XBB.1.5 cases (70% [30-87%] and 48% [7-71%], respectively, for recipients of ≥4 doses). In contrast, cases infected with XBB/XBB.1.5 had 17% (11-24%) and 40% (19-65%) higher adjusted odds of having experienced 1 and ≥2 prior documented infections, respectively, including with pre-Omicron variants. As immunity acquired from SARS-CoV-2 infection becomes increasingly widespread, fitness costs associated with enhanced vaccine sensitivity in XBB/XBB.1.5 may be offset by increased ability to evade infection-derived host responses.

Quantifying mechanisms of coexistence in disease ecology

Pathogen coexistence depends on ecological processes operating at both within and between-host scales, making it difficult to quantify which processes may promote or prevent coexistence. Here, we propose that adapting modern coexistence theory-traditionally applied in plant communities-to pathogen systems provides an exciting approach for examining mechanisms of coexistence operating across different spatial scales. We first overview modern coexistence theory and its mechanistic decomposition; we subsequently adapt the framework to quantify how spatial variation in pathogen density, host resources and immunity, and their interaction may promote pathogen coexistence. We apply this derivation to an example two pathogen, multi-scale model comparing two scenarios with generalist and strain-specific immunity: one with demographic equivalency among pathogens and one with demographic trade-offs among pathogens. We then show how host-pathogen feedbacks generate spatial heterogeneity that promote pathogen coexistence and decompose those mechanisms to quantify how each spatial heterogeneity contributes to that coexistence. Specifically, coexistence of demographically equivalent pathogens occurs due to spatial variation in host resources, immune responses, and pathogen aggregation. With a competition-colonization trade-off, the superior colonizer requires spatial heterogeneity to coexist, whereas the superior competitor does not. Finally, we suggest ways forward for linking theory and empirical tests of coexistence in disease systems.

Uses of mathematical modeling to estimate the impact of mass drug administration of antibiotics on antimicrobial resistance within and between communities

Background

Antibiotics are a key part of modern healthcare, but their use has downsides, including selecting for antibiotic resistance, both in the individuals treated with antibiotics and in the community at large. When evaluating the benefits and costs of mass administration of azithromycin to reduce childhood mortality, effects of antibiotic use on antibiotic resistance are important but difficult to measure, especially when evaluating resistance that “spills over” from antibiotic-treated individuals to other members of their community. The aim of this scoping review was to identify how the existing literature on antibiotic resistance modeling could be better leveraged to understand the effect of mass drug administration (MDA) on antibiotic resistance.

Main text

Mathematical models of antibiotic use and resistance may be useful for estimating the expected effects of different MDA implementations on different populations, as well as aiding interpretation of existing data and guiding future experimental design. Here, strengths and limitations of models of antibiotic resistance are reviewed, and possible applications of those models in the context of mass drug administration with azithromycin are discussed.

Conclusions

Statistical models of antibiotic use and resistance may provide robust and relevant estimates of the possible effects of MDA on resistance. Mechanistic models of resistance, while able to more precisely estimate the effects of different implementations of MDA on resistance, may require more data from MDA trials to be accurately parameterized.

Graphical Abstract

Serotype 1 pneumococcus: epidemiology, genomics, and disease mechanisms

Streptococcus pneumoniae (the 'pneumococcus') is a significant cause of morbidity and mortality worldwide, causing life-threatening diseases such as pneumonia, bacteraemia, and meningitis, with an annual death burden of over one million. Discovered over a century ago, pneumococcal serotype 1 (S1) is a significant cause of these life-threatening diseases. Our understanding of the epidemiology and biology of pneumococcal S1 has significantly improved over the past two decades, informing the development of preventative and surveillance strategies. However, many questions remain unanswered. Here, we review the current state of knowledge of pneumococcal S1, with a special emphasis on clinical epidemiology, genomics, and disease mechanisms.

Pneumococcal within-host diversity during colonization, transmission and treatment

Characterizing 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 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with 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 that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization 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.

Age-seroprevalence curves for the multi-strain structure of influenza A virus

The relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% - 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% - 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens.

The impact of infection-derived immunity on disease dynamics

When modeling infectious diseases, it is common to assume that infection-derived immunity is either (1) non-existent or (2) perfect and lifelong. However there are many diseases in which infection-derived immunity is known to be present but imperfect. There are various ways in which infection-derived immunity can fail, which can ultimately impact the probability that an individual be reinfected by the same pathogen, as well as the long-run population-level prevalence of the pathogen. Here we discuss seven different models of imperfect infection-derived immunity, including waning, leaky and all-or-nothing immunity. For each model we derive the probability that an infected individual becomes reinfected during their lifetime, given that the system is at endemic equilibrium. This can be thought of as the impact that each of these infection-derived immunity failures have on reinfection. This measure is useful because it provides us with a way to compare different modes of failure of infection-derived immunity.

Why are there so few (or so many) circulating coronaviruses?

Despite vast diversity in non-human hosts and conspicuous recent spillover events, only a small number of coronaviruses have been observed to persist in human populations. This puzzling mismatch suggests substantial barriers to establishment. We detail hypotheses that might contribute to explain the low numbers of endemic coronaviruses, despite their considerable evolutionary and emergence potential. We assess possible explanations ranging from issues of ascertainment, historically lower opportunities for spillover, aspects of human demographic changes, and features of pathogen biology and pre-existing adaptive immunity to related viruses. We describe how successful emergent viral species must triangulate transmission, virulence, and host immunity to maintain circulation. Characterizing the factors that might shape the limits of viral persistence can delineate promising research directions to better understand the combinations of pathogens and contexts that are most likely to lead to spillover.

Modeling the effect of vaccination on selection for antibiotic resistance in Streptococcus pneumonia e

Vaccines against bacterial pathogens can protect recipients from becoming infected with potentially antibiotic-resistant pathogens. However, by altering the selective balance between antibiotic-sensitive and antibiotic-resistant bacterial strains, vaccines may also suppress-or spread-antibiotic resistance among unvaccinated individuals. Predicting the outcome of vaccination requires knowing what drives selection for drug-resistant bacterial pathogens and what maintains the circulation of both antibiotic-sensitive and antibiotic-resistant strains of bacteria. To address this question, we used mathematical modeling and data from 2007 on penicillin consumption and penicillin nonsusceptibility in Streptococcus pneumoniae (pneumococcus) invasive isolates from 27 European countries. We show that the frequency of penicillin resistance in S. pneumoniae can be explained by between-host diversity in antibiotic use, heritable diversity in pneumococcal carriage duration, or frequency-dependent selection brought about by within-host competition between antibiotic-resistant and antibiotic-sensitive S. pneumoniae strains. We used our calibrated models to predict the impact of non-serotype-specific pneumococcal vaccination upon the prevalence of S. pneumoniae carriage, incidence of disease, and frequency of S. pneumoniae antibiotic resistance. We found that the relative strength and directionality of competition between drug-resistant and drug-sensitive pneumococcal strains was the most important determinant of whether vaccination would promote, inhibit, or have little effect upon the evolution of antibiotic resistance. Last, we show that country-specific differences in pathogen transmission substantially altered the predicted impact of vaccination, highlighting that policies for managing antibiotic resistance with vaccines must be tailored to a specific pathogen and setting.

The ratio of single to co-colonization is key to complexity in interacting systems with multiple strains

The high number and diversity of microbial strains circulating in host populations have motivated extensive research on the mechanisms that maintain biodiversity. However, much of this work focuses on strain-specific and cross-immunity interactions. Another less explored mode of pairwise interaction is via altered susceptibilities to co-colonization in hosts already colonized by one strain. Diversity in such interaction coefficients enables strains to create dynamically their niches for growth and persistence, and "engineer" their common environment. How such a network of interactions with others mediates collective coexistence remains puzzling analytically and computationally difficult to simulate. Furthermore, the gradients modulating stability-complexity regimes in such multi-player endemic systems remain poorly understood. In a recent study (Madec & Gjini, Bulletin of Mathematical Biology, 82), we obtained an analytic representation for N-type coexistence in an SIS epidemiological model with co-colonization. We mapped multi-strain dynamics to a replicator equation using timescale separation. Here, we examine what drives coexistence regimes in such co-colonization system. We find the ratio of single to co-colonization, µ, critically determines the type of equilibrium and number of coexisting strains, and encodes a trade-off between overall transmission intensity R 0 and mean interaction coefficient in strain space, k. Preserving a given coexistence regime, under fixed trait variation, requires balancing between higher mean competition in favorable environments, and higher cooperation in harsher environments, and is consistent with the stress gradient hypothesis. Multi-strain coexistence tends to steady-state attractors for small µ, whereas as µ increases, dynamics tend to more complex attractors. Following strain frequencies, evolutionary dynamics in the system also display contrasting patterns with µ, interpolating between multi-stable and fluctuating selection for cooperation and mean invasion fitness, in the two extremes. This co-colonization framework could be applied more generally, to study invariant principles in collective coexistence, and to quantify how critical shifts in community dynamics get potentiated by mean-field and environmental gradients.

Understanding the evolution of multiple drug resistance in structured populations

The evolution of multidrug resistance (MDR) is a pressing public health concern. Yet many aspects, such as the role played by population structure, remain poorly understood. Here, we argue that studying MDR evolution by focusing upon the dynamical equations for linkage disequilibrium (LD) can greatly simplify the calculations, generate more insight, and provide a unified framework for understanding the role of population structure. We demonstrate how a general epidemiological model of MDR evolution can be recast in terms of the LD equations. These equations reveal how the different forces generating and propagating LD operate in a dynamical setting at both the population and metapopulation levels. We then apply these insights to show how the LD perspective: (i) explains equilibrium patterns of MDR, (ii) provides a simple interpretative framework for transient evolutionary dynamics, and (iii) can be used to assess the consequences of different drug prescription strategies for MDR evolution.

Negative frequency-dependent selection and asymmetrical transformation stabilise multi-strain bacterial population structures

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.

Mathematical assessment of the impact of cohort vaccination on pneumococcal carriage and serotype replacement

Although pneumococcal vaccines are quite effective in reducing disease burden, factors such as imperfect vaccine efficacy and serotype replacement present an important challenge against realizing direct and herd protection benefits of the vaccines. In this study, a novel mathematical model is designed and used to describe the dynamics of two Streptococcus pneumoniae (SP) serotypes, in response to the introduction of a cohort vaccination program which targets one of the two serotypes. The model is fitted to a pediatric SP carriage prevalence data from Atlanta, GA. The model, which is rigorously analysed to investigate the existence and asymptotic stability properties of the associated equilibria (in addition to exploring conditions for competitive exclusion), is simulated to assess the impact of vaccination under different levels of serotype-specific competition and illustrate the phenomenon of serotype replacement. The calibrated model is used to forecast the carriage prevalence in the pediatric cohort over 30 years.

Pneumococcal Competition Modulates Antibiotic Resistance in the Pre-Vaccination Era: A Modelling Study

The ongoing emergence of antibiotic resistant strains and high frequencies of antibiotic resistance of Streptococcus pneumoniae poses a major public health challenge. How and which ecological and evolutionary mechanisms maintain the coexistence of antibiotic resistant and susceptible strains remains largely an open question. We developed an individual-based, stochastic model expanding on a previous pneumococci modelling framework. We explore how between- and within-host mechanisms of competition can sustain observed levels of resistance to antibiotics in the pre-vaccination era. Our framework considers that within-host competition for co-colonization between resistant and susceptible strains can arise via pre-existing immunity (immunological competition) or intrinsic fitness differences due to resistance costs (ecological competition). We find that beyond stochasticity, population structure or movement, competition at the within-host level can explain observed resistance frequencies. We compare our simulation results to pneumococcal antibiotic resistance data in the European region using approximate Bayesian computation. Our results demonstrate that ecological competition for co-colonization can explain the variation in co-existence of resistant and susceptible pneumococci observed in the pre-vaccination era. Furthermore, we show that within-host pneumococcal competition can facilitate the maintenance of resistance in the pre-vaccination era. Accounting for these competition-related components of pneumococcal dynamics can improve our understanding of drivers for the emergence and maintenance of antibiotic resistance in pneumococci.

Protective Effect of Nasal Colonisation with ∆cps/piaA and ∆cps/proABCStreptococcus pneumoniae Strains against Recolonisation and Invasive Infection

RATIONALE

Nasopharyngeal administration of live virulence-attenuated Streptococcus pneumoniae strains is a potential novel preventative strategy. One target for creating reduced virulence S. pneumoniae strains is the capsule, but loss of the capsule reduces the duration of S. pneumoniae colonisation in mice which could impair protective efficacy against subsequent infection.

OBJECTIVES

To assess protective efficacy of nasopharyngeal administration of unencapsulated S. pneumoniae strains in murine infection models.

METHODS

Strains containing cps locus deletions combined with the S. pneumoniae virulence factors psaA (reduces colonisation) or proABC (no effect on colonisation) were constructed and their virulence phenotypes and ability to prevent recolonisation or invasive infection assessed using mouse infection models. Serological responses to colonisation were compared between strains using ELISAs, immunoblots and 254 S. pneumoniae protein antigen array.

MEASUREMENTS AND MAIN RESULTS

The ∆cps/piaA and ∆cps/proABC strains were strongly attenuated in virulence in both invasive infection models and had a reduced ability to colonise the nasopharynx. ELISAs, immunoblots and protein arrays showed colonisation with either strain stimulated weaker serological responses than the wild type strain. Mice previously colonised with these strains were protected against septicaemic pneumonia but, unlike mice colonised with the wild type strain, not against S. pneumoniae recolonisation.

CONCLUSIONS

Colonisation with the ∆cps/piaA and ∆cps/proABC strains prevented subsequent septicaemia, but in contrast, to published data for encapsulated double mutant strains they did not prevent recolonisation with S. pneumoniae. These data suggest targeting the cps locus is a less effective option for creating live attenuated strains that prevent S. pneumoniae infections.

Nutrient conditions are primary drivers of bacterial capsule maintenance in Klebsiella

The fitness cost associated with the production of bacterial capsules is considered to be offset by the protection provided by these extracellular structures against biotic aggressions or abiotic stress. However, it is unknown if the capsule contributes to fitness in the absence of these. Here, we explored conditions favouring the maintenance of the capsule in Klebsiella pneumoniae, where the capsule is known to be a major virulence factor. Using short-term experimental evolution on different Klebsiella strains, we showed that small environmental variations have a strong impact on the maintenance of the capsule. Capsule inactivation is frequent in nutrient-rich, but scarce in nutrient-poor media. Competitions between wild-type and capsule mutants in nine different strains confirmed that the capsule is costly in nutrient-rich media. Surprisingly, these results also showed that the presence of a capsule provides a clear fitness advantage in nutrient-poor conditions by increasing both growth rates and population yields. The comparative analyses of the wild-type and capsule mutants reveal complex interactions between the environment, genetic background and serotype even in relation to traits known to be relevant during pathogenesis. In conclusion, our data suggest there are novel roles for bacterial capsules yet to be discovered and further supports the notion that the capsule's role in virulence may be a by-product of its contribution to bacterial adaptation outside the host.

Cross-reactivity of antibody responses to Borrelia afzelii OspC: Asymmetry and host heterogeneity

The tick-transmitted bacterium Borrelia afzelii consists of a number of antigenically different strains - often defined by outer surface protein C (OspC) genotype - that coexist at stable frequencies in host populations. To investigate how host antibody responses affect strain coexistence, we measured antibody cross-reactivity to three different OspC types (OspC 2, 3 and 9) in three different strains of laboratory mice (BALB/c, C3H and C57BL/6). The extent of cross-reactivity differed between mouse strains, being higher in C3H than BALB/c and C57BL/6. In one of three pairwise comparisons of OspC types (OspC2 vs OspC9), there was evidence for asymmetry of cross-reactivity, with antibodies to OspC2 cross-reacting more strongly with OspC9 than vice versa. These results indicate that the extent of antibody-mediated competition between OspC types may depend on the composition of the host population, and that such competition may be asymmetric. We discuss the implications of these results for understanding the coexistence of OspC types.

The microbiota in pneumonia: From protection to predisposition

Mucosal surfaces of the upper respiratory tract and gut are physiologically colonized with their own collection of microbes, the microbiota. The normal upper respiratory tract and gut microbiota protects against pneumonia by impeding colonization by potentially pathogenic bacteria and by regulating immune responses. However, antimicrobial therapy and critical care procedures perturb the microbiota, thus compromising its function and predisposing to lung infections (pneumonia). Interindividual variations and age-related alterations in the microbiota also affect vulnerability to pneumonia. We discuss how the healthy microbiota protects against pneumonia and how host factors and medical interventions alter the microbiota, thus influencing susceptibility to pneumonia.

Evolutionary Genetics of Borrelia

The genus Borrelia consists of evolutionarily and genetically diverse bacterial species that cause a variety of diseases in humans and domestic animals. These vector-borne spirochetes can be classified into two major evolutionary groups, the Lyme borreliosis clade and the relapsing fever clade, both of which have complex transmission cycles during which they interact with multiple host species and arthropod vectors. Molecular, ecological, and evolutionary studies have each provided significant contributions towards our understanding of the natural history, biology and evolutionary genetics of Borrelia species; however, integration of these studies is required to identify the evolutionary causes and consequences of the genetic variation within and among Borrelia species. For example, molecular and genetic studies have identified the adaptations that maximize fitness components throughout the Borrelia lifecycle and enhance transmission efficacy but provide limited insights into the evolutionary pressures that have produced them. Ecological studies can identify interactions between Borrelia species and the vertebrate hosts and arthropod vectors they encounter and the resulting impact on the geographic distribution and abundance of spirochetes but not the genetic or molecular basis underlying these interactions. In this review we discuss recent findings on the evolutionary genetics from both of the evolutionarily distinct clades of Borrelia species. We focus on connecting molecular interactions to the ecological processes that have driven the evolution and diversification of Borrelia species in order to understand the current distribution of genetic and molecular variation within and between Borrelia species.

Evolutionary ecology of Lyme Borrelia

The bacterial genus, Borrelia, is comprised of vector-borne spirochete species that infect and are transmitted from multiple host species. Some Borrelia species cause highly-prevalent diseases in humans and domestic animals. Evolutionary, ecological, and molecular research on many Borrelia species have resulted in tremendous progress toward understanding the biology and natural history of these species. Yet, many outstanding questions, such as how Borrelia populations will be impacted by climate and land-use change, will require an interdisciplinary approach. The evolutionary ecology research framework incorporates theory and data from evolutionary, ecological, and molecular studies while overcoming common assumptions within each field that can hinder integration across these disciplines. Evolutionary ecology offers a framework to evaluate the ecological consequences of evolved traits and to predict how present-day ecological processes may result in further evolutionary change. Studies of microbes with complex transmission cycles, like Borrelia, which interact with multiple vertebrate hosts and arthropod vectors, are poised to leverage the power of the evolutionary ecology framework to identify the molecular interactions involved in ecological processes that result in evolutionary change. Using existing data, we outline how evolutionary ecology theory can delineate how interactions with other species and the physical environment create selective forces or impact migration of Borrelia populations and result in micro-evolutionary changes. We further discuss the ecological and molecular consequences of those micro-evolutionary changes. While many of the currently outstanding questions will necessitate new experimental designs and additional empirical data, many others can be addressed immediately by integrating existing molecular and ecological data within an evolutionary ecology framework.

Predicting N-Strain Coexistence from Co-colonization Interactions: Epidemiology Meets Ecology and the Replicator Equation

Multi-type infection processes are ubiquitous in ecology, epidemiology and social systems, but remain hard to analyze and to understand on a fundamental level. Here, we study a multi-strain susceptible-infected-susceptible model with coinfection. A host already colonized by one strain can become more or less vulnerable to co-colonization by a second strain, as a result of facilitating or competitive interactions between the two. Fitness differences between N strains are mediated through \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N^2$$\end{document}N2 altered susceptibilities to secondary infection that depend on colonizer-cocolonizer identities (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$K_{ij}$$\end{document}Kij). By assuming strain similarity in such pairwise traits, we derive a model reduction for the endemic system using separation of timescales. This ‘quasi-neutrality’ in trait space sets a fast timescale where all strains interact neutrally, and a slow timescale where selective dynamics unfold. We find that these slow dynamics are governed by the replicator equation for N strains. Our framework allows to build the community dynamics bottom-up from only pairwise invasion fitnesses between members. We highlight that mean fitness of the multi-strain network, changes with their individual dynamics, acts equally upon each type, and is a key indicator of system resistance to invasion. By uncovering the link between N-strain epidemiological coexistence and the replicator equation, we show that the ecology of co-colonization relates to Fisher’s fundamental theorem and to Lotka-Volterra systems. Besides efficient computation and complexity reduction for any system size, these results open new perspectives into high-dimensional community ecology, detection of species interactions, and evolution of biodiversity.

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.

Population structure across scales facilitates coexistence and spatial heterogeneity of antibiotic-resistant infections

Antibiotic-resistant infections are a growing threat to human health, but basic features of the eco-evolutionary dynamics remain unexplained. Most prominently, there is no clear mechanism for the long-term coexistence of both drug-sensitive and resistant strains at intermediate levels, a ubiquitous pattern seen in surveillance data. Here we show that accounting for structured or spatially-heterogeneous host populations and variability in antibiotic consumption can lead to persistent coexistence over a wide range of treatment coverages, drug efficacies, costs of resistance, and mixing patterns. Moreover, this mechanism can explain other puzzling spatiotemporal features of drug-resistance epidemiology that have received less attention, such as large differences in the prevalence of resistance between geographical regions with similar antibiotic consumption or that neighbor one another. We find that the same amount of antibiotic use can lead to very different levels of resistance depending on how treatment is distributed in a transmission network. We also identify parameter regimes in which population structure alone cannot support coexistence, suggesting the need for other mechanisms to explain the epidemiology of antibiotic resistance. Our analysis identifies key features of host population structure that can be used to assess resistance risk and highlights the need to include spatial or demographic heterogeneity in models to guide resistance management.

Estimating the contribution of different age strata to vaccine serotype pneumococcal transmission in the pre vaccine era: a modelling study

BACKGROUND

Herd protection through interruption of transmission has contributed greatly to the impact of pneumococcal conjugate vaccines (PCVs) and may enable the use of cost-saving reduced dose schedules. To aid PCV age targeting to achieve herd protection, we estimated which population age groups contribute most to vaccine serotype (VT) pneumococcal transmission.

METHODS

We used transmission dynamic models to mirror pre-PCV epidemiology in England and Wales, Finland, Kilifi in Kenya and Nha Trang in Vietnam where data on carriage prevalence in infants, pre-school and school-aged children and adults as well as social contact patterns was available. We used Markov Chain Monte Carlo methods to fit the models and then extracted the per capita and population-based contribution of different age groups to VT transmission.

RESULTS

We estimated that in all settings, < 1-year-old infants cause very frequent secondary vaccine type pneumococcal infections per capita. However, 1-5-year-old children have the much higher contribution to the force of infection at 51% (28, 73), 40% (27, 59), 37% (28, 48) and 67% (41, 86) of the total infection pressure in E&W, Finland, Kilifi and Nha Trang, respectively. Unlike the other settings, school-aged children in Kilifi were the dominant source for VT infections with 42% (29, 54) of all infections caused. Similarly, we estimated that the main source of VT infections in infants are pre-school children and that in Kilifi 39% (28, 51) of VT infant infections stem from school-aged children whereas this was below 15% in the other settings.

CONCLUSION

Vaccine protection of pre-school children is key for PCV herd immunity. However, in high transmission settings, school-aged children may substantially contribute to transmission and likely have waned much of their PCV protection under currently recommended schedules.

Epidemiological consequences of enduring strain-specific immunity requiring repeated episodes of infection

Group A Streptococcus (GAS) skin infections are caused by a diverse array of strain types and are highly prevalent in disadvantaged populations. The role of strain-specific immunity in preventing GAS infections is poorly understood, representing a critical knowledge gap in vaccine development. A recent GAS murine challenge study showed evidence that sterilising strain-specific and enduring immunity required two skin infections by the same GAS strain within three weeks. This mechanism of developing enduring immunity may be a significant impediment to the accumulation of immunity in populations. We used an agent-based mathematical model of GAS transmission to investigate the epidemiological consequences of enduring strain-specific immunity developing only after two infections with the same strain within a specified interval. Accounting for uncertainty when correlating murine timeframes to humans, we varied this maximum inter-infection interval from 3 to 420 weeks to assess its impact on prevalence and strain diversity, and considered additional scenarios where no maximum inter-infection interval was specified. Model outputs were compared with longitudinal GAS surveillance observations from northern Australia, a region with endemic infection. We also assessed the likely impact of a targeted strain-specific multivalent vaccine in this context. Our model produced patterns of transmission consistent with observations when the maximum inter-infection interval for developing enduring immunity was 19 weeks. Our vaccine analysis suggests that the leading multivalent GAS vaccine may have limited impact on the prevalence of GAS in populations in northern Australia if strain-specific immunity requires repeated episodes of infection. Our results suggest that observed GAS epidemiology from disease endemic settings is consistent with enduring strain-specific immunity being dependent on repeated infections with the same strain, and provide additional motivation for relevant human studies to confirm the human immune response to GAS skin infection.

Group A Streptococcus (GAS) is a ubiquitous bacterial pathogen that exists in many distinct strains, and is a major cause of death and disability globally. Vaccines against GAS are under development, but their effective use will require better understanding of how immunity develops following infection. Evidence from an animal model of skin infection suggests that the generation of enduring strain-specific immunity requires two infections by the same strain within a short time frame. It is not clear if this mechanism of immune development operates in humans, nor how it would contribute to the persistence of GAS in populations and affect vaccine impact. We used a mathematical model of GAS transmission, calibrated to data collected in an Indigenous Australian community, to assess whether this mechanism of immune development is consistent with epidemiological observations, and to explore its implications for the impact of a vaccine. We found that it is plausible that repeat infections are required for the development of immunity in humans, and illustrate the difficulties associated with achieving sustained reductions in disease prevalence with a vaccine.

Designing ecologically optimized pneumococcal vaccines using population genomics

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.

Interplay between competitive and cooperative interactions in a three-player pathogen system

In ecological systems, heterogeneous interactions between pathogens take place simultaneously. This occurs, for instance, when two pathogens cooperate, while at the same time, multiple strains of these pathogens co-circulate and compete. Notable examples include the cooperation of human immunodeficiency virus with antibiotic-resistant and susceptible strains of tuberculosis or some respiratory infections with Streptococcus pneumoniae strains. Models focusing on competition or cooperation separately fail to describe how these concurrent interactions shape the epidemiology of such diseases. We studied this problem considering two cooperating pathogens, where one pathogen is further structured in two strains. The spreading follows a susceptible-infected-susceptible process and the strains differ in transmissibility and extent of cooperation with the other pathogen. We combined a mean-field stability analysis with stochastic simulations on networks considering both well-mixed and structured populations. We observed the emergence of a complex phase diagram, where the conditions for the less transmissible, but more cooperative strain to dominate are non-trivial, e.g. non-monotonic boundaries and bistability. Coupled with community structure, the presence of the cooperative pathogen enables the coexistence between strains by breaking the spatial symmetry and dynamically creating different ecological niches. These results shed light on ecological mechanisms that may impact the epidemiology of diseases of public health concern.

Pneumococcal colonisation is an asymptomatic event in healthy adults using an experimental human colonisation model

INTRODUCTION

Pneumococcal colonisation is regarded as a pre-requisite for developing pneumococcal disease. In children previous studies have reported pneumococcal colonisation to be a symptomatic event and described a relationship between symptom severity/frequency and colonisation density. The evidence for this in adults is lacking in the literature. This study uses the experimental human pneumococcal challenge (EHPC) model to explore whether pneumococcal colonisation is a symptomatic event in healthy adults.

METHODS

Healthy participants aged 18-50 were recruited and inoculated intra-nasally with either Streptococcus pneumoniae (serotypes 6B, 23F) or saline as a control. Respiratory viral swabs were obtained prior to inoculation. Nasal and non-nasal symptoms were then assessed using a modified Likert score between 1 (no symptoms) to 7 (cannot function). The rate of symptoms reported between the two groups was compared and a correlation analysis performed.

RESULTS

Data from 54 participants were analysed. 46 were inoculated with S. pneumoniae (29 with serotype 6B, 17 with serotype 23F) and 8 received saline (control). In total, 14 became experimentally colonised (30.4%), all of which were inoculated with serotype 6B. There was no statistically significant difference in nasal (p = 0.45) or non-nasal symptoms (p = 0.28) between the inoculation group and the control group. In those who were colonised there was no direct correlation between colonisation density and symptom severity. In the 22% (12/52) who were co-colonised, with pneumococcus and respiratory viruses, there was no statistical difference in either nasal or non-nasal symptoms (virus positive p = 0.74 and virus negative p = 1.0).

CONCLUSION

Pneumococcal colonisation using the EHPC model is asymptomatic in healthy adults, regardless of pneumococcal density or viral co-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.

Maternal Antibodies Provide Bank Voles with Strain-Specific Protection against Infection by the Lyme Disease Pathogen

Multistrain microbial pathogens often induce strain-specific antibody responses in their vertebrate hosts. Mothers can transmit antibodies to their offspring, which can provide short-term, strain-specific protection against infection. Few experimental studies have investigated this phenomenon for multiple strains of zoonotic pathogens occurring in wildlife reservoir hosts. The tick-borne bacterium Borrelia afzelii causes Lyme disease in Europe and consists of multiple strains that cycle between the tick vector (Ixodes ricinus) and vertebrate hosts, such as the bank vole (Myodes glareolus). We used a controlled experiment to show that female bank voles infected with B. afzelii via tick bite transmit protective antibodies to their offspring. To test the specificity of protection, the offspring were challenged using a natural tick bite challenge with either the maternal strain to which the mothers had been exposed or a different strain. The maternal antibodies protected the offspring against a homologous infectious challenge but not against a heterologous infectious challenge. The offspring from the uninfected control mothers were equally susceptible to both strains. Borrelia outer surface protein C (OspC) is an antigen that is known to induce strain-specific immunity. Maternal antibodies in the offspring reacted more strongly with homologous than with heterologous recombinant OspC, but other antigens may also mediate strain-specific immunity. Our study shows that maternal antibodies provide strain-specific protection against B. afzelii in an ecologically important rodent reservoir host. The transmission of maternal antibodies may have important consequences for the epidemiology of multistrain pathogens in nature.IMPORTANCE Many microbial pathogen populations consist of multiple strains that induce strain-specific antibody responses in their vertebrate hosts. Females can transmit these antibodies to their offspring, thereby providing them with short-term strain-specific protection against microbial pathogens. We investigated this phenomenon using multiple strains of the tick-borne microbial pathogen Borrelia afzelii and its natural rodent reservoir host, the bank vole, as a model system. We found that female bank voles infected with B. afzelii transmitted to their offspring maternal antibodies that provided highly efficient but strain-specific protection against a natural tick bite challenge. The transgenerational transfer of antibodies could be a mechanism that maintains the high strain diversity of this tick-borne pathogen in nature.

The Impact of the 13-Valent Pneumococcal Conjugate Vaccine on Pneumococcal Carriage in the Community Acquired Pneumonia Immunization Trial in Adults (CAPiTA) Study

Background

The impact of pneumococcal conjugate vaccination on the prevalence of nasopharyngeal carriage with pneumococci and other bacteria in adults is unknown. The direct effects of the 13-valent pneumococcal conjugate vaccine (PCV13) in community dwelling older adults was investigated as part of the randomized controlled Community Acquired Pneumonia immunization Trial in Adults (CAPiTA).

Methods

We determined the carriage of Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, and Moraxella catarrhalis before and 6, 12, and 24 months after vaccination using polymerase chain reaction (PCR)-based methods and conventional cultures of nasopharyngeal and oropharyngeal swab samples in 1006 PCV13 recipients and 1005 controls. Serotyping of the 13 vaccine-type (VT) pneumococci was performed by PCR targeting capsular synthesis genes and Quellung reaction of isolates.

Results

Before randomization and based on PCR, 339 of 1891 subjects had nasopharyngeal carriage with any pneumococci (17.9%), and 114 of 1891 (6.0%) carried VT pneumococci. At 6 months after vaccination, VT pneumococcal carriage was significantly lower in PCV13 recipients than in the placebo group (relative risk, 0.53; 95% confidence interval, .35-.80; P = .04). There was no difference between the groups at 12 and 24 months after vaccination. Carriage of non-VT pneumococci, S. aureus, H. influenzae, and M. catarrhalis did not change between groups.

Conclusions

In community-dwelling adults aged ≥65 years, a single dose of PCV13 seems to elicit a small and temporary reduction in VT carriage 6 months after vaccination. Neither replacement by non-VT serotypes nor impact on other nasopharyngeal bacteria was observed.

Innate and adaptive nasal mucosal immune responses following experimental human pneumococcal colonization

Streptococcus pneumoniae (Spn) is a common cause of respiratory infection, but also frequently colonizes the nasopharynx in the absence of disease. We used mass cytometry to study immune cells from nasal biopsy samples collected following experimental human pneumococcal challenge in order to identify immunological mechanisms of control of Spn colonization. Using 37 markers, we characterized 293 nasal immune cell clusters, of which 7 were associated with Spn colonization. B cell and CD161⁺CD8⁺ T cell clusters were significantly lower in colonized than in noncolonized subjects. By following a second cohort before and after pneumococcal challenge we observed that B cells were depleted from the nasal mucosa upon Spn colonization. This associated with an expansion of Spn polysaccharide–specific and total plasmablasts in blood. Moreover, increased responses of blood mucosa-associated invariant T (MAIT) cells against in vitro stimulation with pneumococcus prior to challenge associated with protection against establishment of Spn colonization and with increased mucosal MAIT cell populations. These results implicate MAIT cells in the protection against pneumococcal colonization and demonstrate that colonization affects mucosal and circulating B cell populations.

Estimated impact of revising the 13-valent pneumococcal conjugate vaccine schedule from 2+1 to 1+1 in England and Wales: A modelling study

BACKGROUND

In October 2017, the United Kingdom Joint Committee on Vaccination and Immunisation (JCVI) recommended removal of one primary dose of the 13-valent pneumococcal conjugate vaccine (PCV13) from the existing 2+1 schedule (2, 4, 12 months). We conducted a mathematical modelling study to investigate the potential impact of a 1+1 (3, 12 month) schedule on invasive pneumococcal disease (IPD) and pneumococcal community-acquired pneumonia (CAP). Our results and those from a 1+1 immunogenicity study formed the key evidence reviewed by JCVI.

METHODS AND FINDINGS

We developed age-structured, dynamic, deterministic models of pneumococcal transmission in England and Wales to describe the impact on IPD of 7-valent PCV (PCV7; introduced in 2006) and PCV13 (introduced in 2010). Key transmission and vaccine parameters were estimated by fitting to carriage data from 2001/2002 and post-PCV IPD data to 2015, using vaccine coverage, mixing patterns between ages, and population data. We considered various models to investigate potential reasons for the rapid increase in non-PCV13 (non-vaccine serotype [NVT]) IPD cases since 2014. After searching a large parameter space, 500 parameter sets were identified with a likelihood statistically close to the maximum and these used to predict future cases (median, prediction range from 500 parameter sets). Our findings indicated that the emergence of individual NVTs with higher virulence resulting from ongoing replacement was likely responsible; the NVT increase was predicted to plateau from 2020. Long-term simulation results suggest that changing to a 1+1 schedule would have little overall impact, as the small increase in vaccine-type IPD would be offset by a reduction in NVT IPD. Our results were robust to changes in vaccine assumptions in a sensitivity analysis. Under the base case scenario, a change to a 1+1 schedule in 2018 was predicted to produce 31 (6, 76) additional IPD cases over five years and 83 (-10, 242) additional pneumococcal-CAP cases, with together 8 (-2, 24) additional deaths, none in children under 15 years. Long-term continuation with the 2+1 schedule, or changing to a 1+1, was predicted to sustain current reductions in IPD cases in under-64-year-olds, but cases in 65+-year-olds would continue to increase because of the effects of an aging population. Limitations of our model include difficulty in fitting to past trends in NVT IPD in some age groups and inherent uncertainty about future NVT behaviour, sparse data for defining the mixing matrix in 65+-year-olds, and the methodological challenge of defining uncertainty on predictions.

CONCLUSIONS

Our findings suggest that, with the current mature status of the PCV programme in England and Wales, removing one primary dose in the first year of life would have little impact on IPD or pneumococcal CAP cases or associated deaths at any age. A reduction in the number of priming doses would improve programmatic efficiency and facilitate the introduction of new vaccines by reducing the number of coadministered vaccines given at 2 and 4 months of age in the current UK schedule. Our findings should not be applied to other settings with different pneumococcal epidemiology or with immature programmes and poor herd immunity.

Host contact dynamics shapes richness and dominance of pathogen strains

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains.

On the evolutionary ecology of multidrug resistance in bacteria

Resistance against different antibiotics appears on the same bacterial strains more often than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics and/or bacterial species, whereas the trend is pervasive. Here, we consider the question in terms of strain ecology: explaining why resistance to different antibiotics is often seen on the same strain requires an understanding of the competition between strains with different resistance profiles. This work builds on models originally proposed to explain another aspect of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance between these sub-populations, thus creating niches for sensitivity and resistance. We then generalise this unified underlying model to multidrug resistance and show that models with this structure predict high levels of association between resistance to different drugs and high multidrug resistance frequencies. We test predictions from this model in six bacterial datasets and find them to be qualitatively consistent with observed trends. The higher than expected frequencies of multidrug resistance are often interpreted as evidence that these strains are out-competing strains with lower resistance multiplicity. Our work provides an alternative explanation that is compatible with long-term stability in resistance frequencies.

Herd immunity alters the conditions for performing dose schedule comparisons: an individual-based model of pneumococcal carriage

Background

There is great interest in the use of reduced dosing schedules for pneumococcal conjugate vaccines, a strategy premised on maintaining an acceptable level of protection against disease and carriage of the organism. We asked about the practicality of measuring differential effectiveness against carriage in a population with and without widespread use of the vaccine for infants.

Methods

We adapted an existing transmission-dynamic, individual-based stochastic model fitted to the prevaccine epidemiology of pneumococcal carriage in the United States, and compared the observed vaccine-type carriage prevalence in different arms of a simulated trial with one, two, or three infant doses plus a 12-month booster. Using these simulations, we calculated vaccine efficacy that would be estimated at different times post-enrollment in the trial and calculated required sample sizes to see a difference in carriage prevalence.

Results

In a pneumococcal conjugate vaccine (PCV)-naïve population, the difference in vaccine-type (VT) pneumococcal carriage prevalence between trial arms was less than 7% and varied with sampling time. In a population already receiving routine PCV administration, VT pneumococcal prevalence is nearly indistinguishable between trial arms. Relative efficacy of different dosing schedules was strongly dependent on the time between enrollment and sampling, with maximal prevalence differences reached 1–3 years post-enrollment. Moreover, vaccine efficacy estimates were typically slightly higher in trials in communities already receiving vaccination. Despite this, much larger sample sizes—by more than an order of magnitude—are required for a vaccine trial conducted in a population receiving routine PCV administration as compared to in a PCV-naïve population.

Conclusions

These findings highlight some underappreciated aspects of clinical trials of pneumococcal conjugate vaccines with efficacy endpoints, such as the context- and time-dependence of efficacy estimates. They support the wisdom of conducting comparative dose schedule trials of conjugate vaccine effects on carriage in vaccine-naïve populations.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-3833-6) contains supplementary material, which is available to authorized users.

Mechanisms of Naturally Acquired Immunity to Streptococcus pneumoniae

In this review we give an update on the mechanisms of naturally acquired immunity against Streptococcus pneumoniae, one of the major human bacterial pathogens that is a common cause of pneumonia, septicaemia, and meningitis. A clear understanding of the natural mechanisms of immunity to S. pneumoniae is necessary to help define why the very young and elderly are at high risk of disease, and for devising new prevention strategies. Recent data has shown that nasopharynx colonization by S. pneumoniae induces antibody responses to protein and capsular antigens in both mice and humans, and also induces Th17 CD4+ cellular immune responses in mice and increases pre-existing responses in humans. These responses are protective, demonstrating that colonization is an immunizing event. We discuss the data from animal models and humans on the relative importance of naturally acquired antibody and Th17 cells on immunity to S. pneumoniae at three different anatomical sites of infection, the nasopharynx (the site of natural asymptomatic carriage), the lung (site of pneumonia), and the blood (site of sepsis). Mouse data suggest that CD4+ Th17 cells prevent both primary and secondary nasopharyngeal carriage with no role for antibody induced by previous colonization. In contrast, antibody is necessary for prevention of sepsis but CD4+ cellular responses are not. Protection against pneumonia requires a combination of both antibody and Th17 cells, in both cases targeting protein rather than capsular antigen. Proof of which immune component prevents human infection is less easily available, but two recent papers demonstrate that human IgG targeting S. pneumoniae protein antigens is highly protective against septicaemia. The role of CD4+ responses to prior nasopharyngeal colonization for protective immunity in humans is unclear. The evidence that there is significant naturally-acquired immunity to S. pneumoniae independent of anti-capsular polysaccharide has clinical implications for the detection of subjects at risk of S. pneumoniae infections, and the data showing the importance of protein antigens as targets for antibody and Th17 mediated immunity should aid the development of new vaccine strategies.

Within-host dynamics shape antibiotic resistance in commensal bacteria

The spread of antibiotic resistance, a major threat to human health, is poorly understood. Simple population-level models of bacterial transmission predict that above a certain rate of antibiotic consumption in a population, resistant bacteria should completely eliminate non-resistant strains, while below this threshold they should be unable to persist at all. This prediction stands at odds with empirical evidence showing that resistant and non-resistant strains coexist stably over a wide range of antibiotic consumption rates. Not knowing what drives this long-term coexistence is a barrier to developing evidence-based strategies for managing the spread of resistance. Here, we argue that competition between resistant and sensitive pathogens within individual hosts gives resistant pathogens a relative fitness benefit when they are rare, promoting coexistence between strains at the population level. To test this hypothesis, we embed mechanistically explicit within-host dynamics in a structurally neutral pathogen transmission model. Doing so allows us to reproduce patterns of resistance observed in the opportunistic pathogens Escherichia coli and Streptococcus pneumoniae across European countries and to identify factors that may shape resistance evolution in bacteria by modulating the intensity and outcomes of within-host competition.

Diversity-Generating Machines: Genetics of Bacterial Sugar-Coating

Bacterial pathogens and commensals are surrounded by diverse surface polysaccharides which include capsules and lipopolysaccharides. These carbohydrates play a vital role in bacterial ecology and interactions with the environment. Here, we review recent rapid advancements in this field, which have improved our understanding of the roles, structures, and genetics of bacterial polysaccharide antigens. Genetic loci encoding the biosynthesis of these antigens may have evolved as bacterial diversity-generating machines, driven by selection from a variety of forces, including host immunity, bacteriophages, and cell-cell interactions. We argue that the high adaptive potential of polysaccharide antigens should be taken into account in the design of polysaccharide-targeting medical interventions like conjugate vaccines and phage-based therapies.

Global emergence and population dynamics of divergent serotype 3 CC180 pneumococci

Streptococcus pneumoniae serotype 3 remains a significant cause of morbidity and mortality worldwide, despite inclusion in the 13-valent pneumococcal conjugate vaccine (PCV13). Serotype 3 increased in carriage since the implementation of PCV13 in the USA, while invasive disease rates remain unchanged. We investigated the persistence of serotype 3 in carriage and disease, through genomic analyses of a global sample of 301 serotype 3 isolates of the Netherlands3-31 (PMEN31) clone CC180, combined with associated patient data and PCV utilization among countries of isolate collection. We assessed phenotypic variation between dominant clades in capsule charge (zeta potential), capsular polysaccharide shedding, and susceptibility to opsonophagocytic killing, which have previously been associated with carriage duration, invasiveness, and vaccine escape. We identified a recent shift in the CC180 population attributed to a lineage termed Clade II, which was estimated by Bayesian coalescent analysis to have first appeared in 1968 [95% HPD: 1939-1989] and increased in prevalence and effective population size thereafter. Clade II isolates are divergent from the pre-PCV13 serotype 3 population in non-capsular antigenic composition, competence, and antibiotic susceptibility, the last of which resulting from the acquisition of a Tn916-like conjugative transposon. Differences in recombination rates among clades correlated with variations in the ATP-binding subunit of Clp protease, as well as amino acid substitutions in the comCDE operon. Opsonophagocytic killing assays elucidated the low observed efficacy of PCV13 against serotype 3. Variation in PCV13 use among sampled countries was not independently correlated with the CC180 population shift; therefore, genotypic and phenotypic differences in protein antigens and, in particular, antibiotic resistance may have contributed to the increase of Clade II. Our analysis emphasizes the need for routine, representative sampling of isolates from disperse geographic regions, including historically under-sampled areas. We also highlight the value of genomics in resolving antigenic and epidemiological variations within a serotype, which may have implications for future vaccine development.

Use of an individual-based model of pneumococcal carriage for planning a randomized trial of a whole-cell vaccine

For encapsulated bacteria such as Streptococcus pneumoniae, asymptomatic carriage is more common and longer in duration than disease, and hence is often a more convenient endpoint for clinical trials of vaccines against these bacteria. However, using a carriage endpoint entails specific challenges. Carriage is almost always measured as prevalence, whereas the vaccine may act by reducing incidence or duration. Thus, to determine sample size requirements, its impact on prevalence must first be estimated. The relationship between incidence and prevalence (or duration and prevalence) is convex, saturating at 100% prevalence. For this reason, the proportional effect of a vaccine on prevalence is typically less than its proportional effect on incidence or duration. This relationship is further complicated in the presence of multiple pathogen strains. In addition, host immunity to carriage accumulates rapidly with frequent exposures in early years of life, creating potentially complex interactions with the vaccine’s effect. We conducted a simulation study to predict the impact of an inactivated whole cell pneumococcal vaccine—believed to reduce carriage duration—on carriage prevalence in different age groups and trial settings. We used an individual-based model of pneumococcal carriage that incorporates relevant immunological processes, both vaccine-induced and naturally acquired. Our simulations showed that for a wide range of vaccine efficacies, sampling time and age at vaccination are important determinants of sample size. There is a window of favorable sampling times during which the required sample size is relatively low, and this window is prolonged with a younger age at vaccination, and in a trial setting with lower transmission intensity. These results illustrate the ability of simulation studies to inform the planning of vaccine trials with carriage endpoints, and the methods we present here can be applied to trials evaluating other pneumococcal vaccine candidates or comparing alternative dosing schedules for the existing conjugate vaccines.

Streptococcus pneumoniae, a bacterium carried in the nasopharynx of many healthy people, is also a leading cause of bacterial pneumonia, sepsis, and ear infections in children aged five years and younger. Vaccines targeting select strains of S. pneumoniae have been effective, and the development of new vaccines, particularly those that target all strains, can further lower disease burden. For clinical trials of these vaccines, the number of study participants needed depends on the expected effect of the vaccine on a conveniently measured outcome: asymptomatic carriage. The most economical way to test a vaccine for its effect on carriage is by measuring prevalence at a specific time, and comparing vaccinated to unvaccinated participants. The relationship between incidence (or duration) and prevalence is complex, and changes with time as children develop natural immunity. We explored this relationship using a mathematical model. Given a vaccine efficacy, our computer simulations predict that fewer study participants are needed if they are vaccinated at a younger age, taken from a population with intermediate levels of transmission, and sampled for carriage at a certain time window: 9 to 18 months after vaccination. Our study illustrates how simulation studies can help plan more efficient vaccine trials.