Local adaptation in the Linum marginale-Melampsora lini host-pathogen interaction

The potential for local adaptation between pathogens and their hosts has generated strong theoretical and empirical interest with evidence both for and against local adaptation reported for a range of systems. We use the Linum marginale-Melampsora lini plant-pathogen system and a hierarchical spatial structure to investigate patterns of local adaptation within a metapopulation characterised by epidemic dynamics and frequent extinction of pathogen populations. Based on large sample sizes and comprehensive cross-inoculation trials, our analyses demonstrate strong local adaptation by Melampsora to its host populations, with this effect being greatest at regional scales, as predicted from the broader spatial scales at which M. lini disperses relative to L. marginale. However, there was no consistent trend for more distant pathogen populations to perform more poorly. Our results further show how the coevolutionary interaction between hosts and pathogens can be influenced by local structure such that resistant hosts select for generally virulent pathogens, while susceptible hosts select for more avirulent pathogens. Empirically, local adaptation has generally been tested in two contrasting ways: (1) pathogen performance on sympatric versus allopatric hosts; and (2) sympatric versus allopatric pathogens on a given host population. In situations where no host population is more resistant or susceptible than others when averaged across pathogen populations (and likewise, no pathogen population is more virulent or avirulent than others), results from these tests should generally be congruent. We argue that this is unlikely to be the case in the metapopulation situations that predominate in natural host-pathogen interactions, thus requiring tests that control simultaneously for variation in plant and pathogen populations.     

Spatiotemporal Model of Barley and Cereal Yellow Dwarf Virus Transmission Dynamics with Seasonality and Plant Competition

Many generalist pathogens are influenced by the spatial distributions and relative abundances of susceptible host species. The spatial structure of host populations can influence patterns of infection incidence (or disease outbreaks), and the effects of a generalist pathogen on host community dynamics in a spatially heterogeneous community may differ from predictions derived via simple models. In this paper, we model the transmission of a generalist pathogen within a patch framework that incorporates the movement of vectors between discrete host patches to investigate the effects of local host community composition and vector movement rates on disease dynamics.     

Virulence evolution at the front line of spreading epidemics

Understanding and predicting the spatial spread of emerging pathogens is a major challenge for the public health management of infectious diseases. Theoretical epidemiology shows that the speed of an epidemic is governed by the life‐history characteristics of the pathogen and its ability to disperse. Rapid evolution of these traits during the invasion may thus affect the speed of epidemics. Here we study the influence of virulence evolution on the spatial spread of an epidemic. At the edge of the invasion front, we show that more virulent and transmissible genotypes are expected to win the competition with other pathogens. Behind the front line, however, more prudent exploitation strategies outcompete virulent pathogens. Crucially, even when the presence of the virulent mutant is limited to the edge of the front, the invasion speed can be dramatically altered by pathogen evolution. We support our analysis with individual‐based simulations and we discuss the additional effects of demographic stochasticity taking place at the front line on virulence evolution. We confirm that an increase of virulence can occur at the front, but only if the carrying capacity of the invading pathogen is large enough. These results are discussed in the light of recent empirical studies examining virulence evolution at the edge of spreading epidemics.     

Evaluating the importance of within- and between-host selection pressures on the evolution of chronic pathogens

Infectious pathogens compete and are subject to natural selection at multiple levels. For example, viral strains compete for access to host resources within an infected host and, at the same time, compete for access to susceptible hosts within the host population. Here we propose a novel approach to study the interplay between within- and between-host competition. This approach allows for a single host to be infected by and transmit two strains of the same pathogen. We do this by nesting a model for the host–pathogen dynamics within each infected host into an epidemiological model. The nesting of models allows the between-host infectivity and mortality rates suffered by infected hosts to be functions of the disease progression at the within-host level. We present a general method for computing the basic reproduction ratio of a pathogen in such a model. We then illustrate our method using a basic model for the within-host dynamics of viral infections, embedded within the simplest susceptible–infected (SI) epidemiological model. Within this nested framework, we show that the virion production rate at the level of the cell–virus interaction leads, via within-host competition, to the presence or absence of between-host level competitive exclusion. In particular, we find that in the absence of mutation the strain that maximizes between-host fitness can outcompete all other strains. In the presence of mutation we observe a complex invasion landscape showing the possibility of coexistence. Although we emphasize the application to human viral diseases, we expect this methodology to be applicable to be many host–parasite systems.     

Evolution of airborne infectious diseases according to changes in characteristics of the host population

The authors predicted evolutionary changes in airborne infectious diseases according to changes in the characteristics of the host population. The predictions were based upon a mathematical model of infectious diseases and the validity of the predictions was verified against the history of man and pathogens. The feature of this model is that it involves a density of pathogens in the environment as an additional variable which can be regarded as more suitable to airborne infectious diseases. In spite of this modification, this study reached a similar conclusion to the threshold density theory: that is, susceptible host density in the absence of the pathogen must be larger than that in the presence of the pathogen, for the pathogen to be persistent. Moreover the authors concluded that one type of pathogen cannot be replaced by another type of pathogen as long as the susceptible host density of the former type is the mininum one. The predictions were considered to be valid for a wide range of infectous diseases. Making use of these principles, the authors predicted that the variety of infectious diseases should increase as host density increases and that pathogens should evolve to be less virulent as the host life-span increases. The finalidea discussed is whether or nor the history of man and pathogen can be verified by the predictions.     

Floquet theory for seasonal environmental forcing of spatially explicit waterborne epidemics

The transmission of waterborne pathogens is a complex process that is heavily linked to the spatial characteristics of the underlying environmental matrix as well as to the temporal variability of the relevant hydroclimatological drivers. In this work, we propose a time-varying, spatially explicit network model for the dynamics of waterborne diseases. Applying Floquet theory, which allows to extend results of local stability analysis to periodic dynamical systems, we find conditions for pathogen invasion and establishment in systems characterized by fluctuating environmental forcing, thus extending to time-varying contexts the generalized reproduction numbers recently obtained for spatially explicit epidemiology of waterborne disease. We show that temporal variability may have multifaceted effects on the invasion threshold, as it can either favor pathogen invasion or make it less likely. Moreover, environmental fluctuations characterized by distinctive geographical signatures can produce diversified, highly nontrivial effects on pathogen invasion. Our study is complemented by numerical simulations, which show that pathogen establishment is neither necessary nor sufficient for large epidemic outbreaks to occur in time-varying environments. Finally, we show that our framework can be used to reliably characterize the early geography of epidemic outbreaks triggered by fluctuating environmental conditions.     

The social evolution of bacterial pathogenesis

Many of the genes responsible for the virulence of bacterial pathogens are carried by mobile genetic elements that can be transferred horizontally between different bacterial lineages. Horizontal transfer of virulence-factor genes has played a profound role in the evolution of bacterial pathogens, but it is poorly understood why these genes are so often mobile. Here, I present a hypothetical selective mechanism maintaining virulence-factor genes on horizontally transmissible genetic elements. For virulence factors that are secreted extracellularly, selection within hosts may favour mutant 'cheater' strains of the pathogen that do not produce the virulence factor themselves but still benefit from factors produced by other members of the pathogen population within a host. Using simple mathematical models, I show that if this occurs then selection for infectious transmission between hosts favours pathogen strains that can reintroduce functional copies of virulence-factor genes into cheaters via horizontal transfer, forcing them to produce the virulence factor. Horizontal gene transfer is thus a novel mechanism for the evolution of cooperation. I discuss predictions of this hypothesis that can be tested empirically and its implications for the evolution of pathogen virulence.     

Transmission of Plodia interpunctella granulosis virus does not conform to the mass action model

1. Transmission of insect pathogens is traditionally described by a term which states that transmission is proportional to the densities of the susceptible hosts and the infectious units, multiplied by a constant, the transmission coefficient. Theoretical studies suggest that deviations from this can be important in host–pathogen population dynamics, but little is known of how commonly pathogen transmission conforms to the conventional model.
2. We describe a test of the traditional assumption for the Indian meal moth, Plodia interpunctella (Lepidoptera: Pyralidae) (Hübner) and its granulosis virus using a modification of the previous methods, which allows for unpredictable declines in the amount of infectious material present.
3. The estimated transmission coefficient increased with the density of susceptible hosts and showed a marked decline with density of infectious cadavers. This suggests that the usual assumption does not adequately describe transmission in this system.
4. The reasons for this deviation from the usual assumption are likely to be a combination of behavioural and physiological changes at high host density, and differential susceptibility to the pathogen leading to an effect analogous to pseudo-interference in parasitoids.     

Host immune responses accelerate pathogen evolution

Pathogens face a hostile and often novel environment when infecting a new host, and adaptation is likely to be an important determinant of the success in colonization and establishment. We hypothesized that resistant hosts will impose stronger selection on pathogens than susceptible hosts, which should accelerate pathogen evolution through selection biased toward effector genes. To test this hypothesis, we conducted an experimental evolution study on Xanthomonas citri subsp. citri (Xcc) in a susceptible plant species and a resistant plant species. We performed 55 rounds of repeated reinoculation of Xcc through susceptible host grapefruit (isolates G1, G2, G3) and resistant host kumquat (isolates K1, K2, K3). Consequently, only K1 and K3 isolates lost their ability to elicit a hypersensitive response (HR) in kumquat. Illumina sequencing of the parental and descendant strains P, G1, G2, G3, K1, K2 and K3 revealed that fixed mutations were biased toward type three secretion system effectors in isolates K1 and K3. Parallel evolution was observed in the K1 and K3 strains, suggesting that the mutations result from selection rather than by random drift. Our results support our hypothesis and suggest that repeated infection of resistant hosts by pathogens should be prevented to avoid selecting for adaptive pathogens.     

THE ORIGIN OF SPECIFICITY BY MEANS OF NATURAL SELECTION: EVOLVED AND NONHOST RESISTANCE IN HOST–PATHOGEN INTERACTIONS

Most species seem to be completely resistant to most pathogens and parasites. This resistance has been called “nonhost resistance” because it is exhibited by species that are considered not to be part of the normal host range of the pathogen. A conceptual model is presented suggesting that failure of infection on nonhosts may be an incidental by‐product of pathogen evolution leading to specialization on their source hosts. This model is contrasted with resistance that results from hosts evolving to resist challenge by their pathogens, either as a result of coevolution with a persistent pathogen or as the result of one‐sided evolution by the host against pathogens that are not self‐sustaining on those hosts. Distinguishing evolved from nonevolved resistance leads to contrasting predictions regarding the relationship between resistance and genetic distance. An analysis of cross‐inoculation experiments suggests that the resistance is often the product of pathogen specialization. Understanding the contrasting evolutionary origins of resistance is critical for studies on the genetics and evolution of host–pathogen interactions in human, agricultural, and natural populations. Research on human infectious disease using animal models may often study resistances that have quite contrasting evolutionary origins, and therefore very different underlying genetic mechanisms.     

The evolutionary consequences of alternative types of imperfect vaccines

The emergence and spread of mutant pathogens that evade the effects of prophylactic interventions, including vaccines, threatens our ability to control infectious diseases globally. Imperfect vaccines (e.g. those used against influenza), while not providing life-long immunity, confer protection by reducing a range of pathogen life-history characteristics; conversely, mutant pathogens can gain an advantage by restoring the same range of traits in vaccinated hosts. Using an SEIR model motivated by equine influenza, we investigate the evolutionary consequences of alternative types of imperfect vaccination, by comparing the spread rate of three types of mutant pathogens, in response to three types of vaccines. All mutant types spread faster in response to a transmission-blocking vaccine, relative to vaccines that reduce the proportion of exposed vaccinated individuals becoming infectious, and to vaccines that reduce the length of the infectious period; this difference increases with increasing vaccine efficacy. We interpret our results using the first published Price equation formulation for an SEIR model, and find that our main result is explained by the effects of vaccines on the equilibrium host distribution across epidemiological classes. In particular, the proportion of vaccinated infectious individuals among all exposed and infectious hosts, which is relatively higher in the transmission-blocking vaccine scenario, is important in explaining the faster spread of mutant strains in response to that vaccine. Our work illustrates the connection between epidemiological and evolutionary dynamics, and the need to incorporate both in order to explain and interpret findings of complicated infectious disease dynamics.     

New insights into virulence evolution in multigroup hosts

Many of the standard predictions in evolutionary epidemiology result from models in which all hosts are equally susceptible to acquiring an infection and equally capable of resisting pathogens once an infection has been established. This contrasts with the empirical reality that natural host populations are typically composed of individuals with various susceptibilities and vulnerabilities to pathogen exploitation that can influence all aspects of a given pathogen's transmission-virulence phenotype. In these structured host settings, host-dependent variation in the virulence-transmission trade-off plays an important role in determining pathogen evolution. By deriving some game-theoretic equilibrium expressions that describe pathogen evolution in heterogeneous host populations, the contribution of host heterogeneity to the direction of evolution in host exploitation is made explicit. Within this framework, qualitative departures from predictions derived from theory utilizing a homogeneous host assumption can be seen as a manifestation of Simpson's paradox in an evolutionary setting. By reconsidering some predictions from homogeneous host theory through the lens of this new perspective, it can be seen that many standard predictions are actually special cases that result when homogeneity in immunity parameters is imposed on host populations.     

Dynamics and genealogy of strains in spatially extended host-pathogen models

We examine the dynamics of evolution in a generic spatial model of a pathogen infecting a population of hosts, or an analogous predator-prey system. Previous studies of this model have found a range of interesting phenomena that differ from the well-mixed version. We extend these studies by examining the spatial and temporal dynamics of strains using genealogical tracing. When transmissibility can evolve by mutation, strains of intermediate transmissibility dominate even though high-transmissibility mutants have a short-term reproductive advantage. Mutant strains continually arise and grow rapidly for many generations but eventually go extinct before dominating the system. We find that, after a number of generations, the mutant pathogen characteristics strongly impact the spatial distribution of their local host environment, even when there are diverse types coexisting. Extinction is due to the depletion of susceptibles in the local environment of these mutant strains. Studies of spatial and genealogical relatedness reveal the self-organized spatial clustering of strains that enables their impact on the local environment. Thus, we find that selection acts against the high-transmissibility strains on long time-scales as a result of the feedback due to environmental change. Our study shows that averages over space or time should not be assumed to adequately describe the evolutionary dynamics of spatially distributed host-pathogen systems.     

Spatial configuration of charge and hydrophobicity tune particle transport through mucus

Mucus is a selectively permeable hydrogel that protects wet epithelia from pathogen invasion and poses a barrier to drug delivery. Determining the parameters of a particle that promote or prevent passage through mucus is critical, as it will enable predictions about the mucosal passage of pathogens and inform the design of therapeutics. The effect of particle net charge and size on mucosal transport has been characterized using simple model particles; however, predictions of mucosal passage remain challenging. Here, we utilize rationally designed peptides to examine the integrated contributions of charge, hydrophobicity, and spatial configuration on mucosal transport. We find that net charge does not entirely predict transport. Specifically, for cationic peptides, the inclusion of hydrophobic residues and the position of charged and hydrophobic residues within the peptide impact mucosal transport. We have developed a simple model of mucosal transport that predicts how previously unexplored amino acid sequences achieve slow versus fast passage through mucus. This model may be used as a basis to predict transport behavior of natural peptide-based particles, such as antimicrobial peptides or viruses, and assist in the engineering of synthetic sequences with desired transport properties.     

Evaluating the importance of within- and between-host selection pressures on the evolution of chronic pathogens

Infectious pathogens compete and are subject to natural selection at multiple levels. For example, viral strains compete for access to host resources within an infected host and, at the same time, compete for access to susceptible hosts within the host population. Here we propose a novel approach to study the interplay between within- and between-host competition. This approach allows for a single host to be infected by and transmit two strains of the same pathogen. We do this by nesting a model for the host-pathogen dynamics within each infected host into an epidemiological model. The nesting of models allows the between-host infectivity and mortality rates suffered by infected hosts to be functions of the disease progression at the within-host level. We present a general method for computing the basic reproduction ratio of a pathogen in such a model. We then illustrate our method using a basic model for the within-host dynamics of viral infections, embedded within the simplest susceptible-infected (SI) epidemiological model. Within this nested framework, we show that the virion production rate at the level of the cell-virus interaction leads, via within-host competition, to the presence or absence of between-host level competitive exclusion. In particular, we find that in the absence of mutation the strain that maximizes between-host fitness can outcompete all other strains. In the presence of mutation we observe a complex invasion landscape showing the possibility of coexistence. Although we emphasize the application to human viral diseases, we expect this methodology to be applicable to be many host-parasite systems.     

Shifting effects of host physiological condition following pathogen establishment

Understanding host persistence with emerging pathogens is essential for conserving populations. Hosts may initially survive pathogen invasions through pre-adaptive mechanisms. However, whether pre-adaptive traits are directionally selected to increase in frequency depends on the heritability and environmental dependence of the trait and the costs of trait maintenance. Body condition is likely an important pre-adaptive mechanism aiding in host survival, although can be seasonally variable in wildlife hosts. We used data collected over 7 years on bat body mass, infection and survival to determine the role of host body condition during the invasion and establishment of the emerging disease, white-nose syndrome. We found that when the pathogen first invaded, bats with higher body mass were more likely to survive, but this effect dissipated following the initial epizootic. We also found that heavier bats lost more weight overwinter, but fat loss depended on infection severity. Lastly, we found mixed support that bat mass increased in the population after pathogen arrival; high annual plasticity in individual bat masses may have reduced the potential for directional selection. Overall, our results suggest that some factors that contribute to host survival during pathogen invasion may diminish over time and are potentially replaced by other host adaptations.     

Seed characteristics and susceptibility to pathogen attack in tree seeds of the Peruvian Amazon

Many studies now suggest that pathogens can cause high levels of mortality in seeds and seedlings. Recruitment from seed to sapling is an important bottleneck for many tree species, and if specialist or generalist pathogens have differential negative effects among species of juvenile trees, then they may have a significant impact on forest community structure. To explore the effects of differential pathogen attack among tropical tree species, we quantified pathogen attack on the seeds of 16 tree species from the southeastern Peruvian Amazon and asked which seed characteristics, including size, hardness, germination time and mode, shade tolerance, and fruit type, were most closely correlated with susceptibility to pathogens. Shade tolerance and seed weight were positively and significantly correlated with susceptibility to pathogen attack by ecological trait regressions (ETRs), and correspondence analysis indicated that there might be increased attack rates in species with brightly colored, pulpy fruits (often dispersed by primates). Only shade tolerance was significantly correlated with pathogen attack when the analyses accounted for phylogenetic relatedness between species. Thus, contrary to standard predictions of size-defense ratios, our results suggest that larger, shade-tolerant seeds tend to be more susceptible to pathogen attack than smaller, light-dependent seeds. Moreover, differential pathogen attack may shape seed community composition, which may affect the successful recruitment of adults.     

Modelling Delta-Notch perturbations during zebrafish somitogenesis

The discovery over the last 15 years of molecular clocks and gradients in the pre-somitic mesoderm of numerous vertebrate species has added significant weight to Cooke and Zeeman's ‘clock and wavefront’ model of somitogenesis, in which a travelling wavefront determines the spatial position of somite formation and the somitogenesis clock controls periodicity (Cooke and Zeeman, 1976). However, recent high-throughput measurements of spatiotemporal patterns of gene expression in different zebrafish mutant backgrounds allow further quantitative evaluation of the clock and wavefront hypothesis. In this study we describe how our recently proposed model, in which oscillator coupling drives the propagation of an emergent wavefront, can be used to provide mechanistic and testable explanations for the following observed phenomena in zebrafish embryos: (a) the variation in somite measurements across a number of zebrafish mutants; (b) the delayed formation of somites and the formation of ‘salt and pepper’ patterns of gene expression upon disruption of oscillator coupling; and (c) spatial correlations in the ‘salt and pepper’ patterns in Delta-Notch mutants. In light of our results, we propose a number of plausible experiments that could be used to further test the model.     

Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints

The factors that determine the origin and fate of cross-species transmission events remain unclear for the majority of human pathogens, despite being central for the development of predictive models and assessing the efficacy of prevention strategies. Here, we describe a flexible Bayesian statistical framework to reconstruct virus transmission between different host species based on viral gene sequences, while simultaneously testing and estimating the contribution of several potential predictors of cross-species transmission. Specifically, we use a generalized linear model extension of phylogenetic diffusion to perform Bayesian model averaging over candidate predictors. By further extending this model with branch partitioning, we allow for distinct host transition processes on external and internal branches, thus discriminating between recent cross-species transmissions, many of which are likely to result in dead-end infections, and host shifts that reflect successful onwards transmission in the new host species. Our approach corroborates genetic distance between hosts as a key determinant of both host shifts and cross-species transmissions of rabies virus in North American bats. Furthermore, our results indicate that geographical range overlap is a modest predictor for cross-species transmission, but not for host shifts. Although our evolutionary framework focused on the multi-host reservoir dynamics of bat rabies virus, it is applicable to other pathogens and to other discrete state transition processes.