Comparing single- vs. mixed-genotype infections of Mycosphaerella graminicola on wheat: effects on pathogen virulence and host tolerance

Mixed-genotype infections (infections of a host by more than one pathogen genotype) are common in plant-pathogen systems. However their impact on the course of the infection and especially on pathogen virulence and host response to infection is poorly understood. We investigated the effects of mixed-genotype infections on several parameters: host resistance and tolerance, as well as pathogen aggressiveness and virulence. For these purposes, we inoculated three wheat lines with three Mycosphaerella graminicola genotypes, alone or in mixtures, in a greenhouse experiment. For some of the mixtures, disease severity and virulence were lower than expected from infection by the same genotypes alone, suggesting that competition between genotypes was reducing their aggressiveness and virulence. One host line was fully resistant, but there were differences in resistance in the other lines. The two host lines that became infected differed slightly in tolerance, but mixed-genotype infections had no effect on host tolerance.     

Functional consequences of genetic diversity in Strongyloides ratti infections

Parasitic nematodes show levels of genetic diversity comparable to other taxa, but the functional consequences of this are not understood. Thus, a large body of theoretical work highlights the potential consequences of parasite genetic diversity for the epidemiology of parasite infections and its possible implications for the evolution of host and parasite populations. However, few relevant empirical data are available from parasites in general and none from parasitic nematodes in particular. Here, we test two hypotheses. First, that different parasitic nematode genotypes vary in life-history traits, such as survivorship and fecundity, which may cause variation in infection dynamics. Second, that different parasitic nematode genotypes interact within the host (either directly or via the host immune system) to increase the mean reproductive output of mixed-genotype infections compared with single-genotype infections. We test these hypotheses in laboratory infections using genetically homogeneous lines of Strongyloides ratti. We find that nematode genotypes do vary in their survivorship and fecundity and, consequently, in their dynamics of infection. However, we find little evidence of interactions between genotypes within hosts under a variety of trickle- and single-infected infection regimes.     

Heterogeneity in susceptibility to infection can explain high reinfection rates

Heterogeneity in susceptibility and infectivity is inherent to infectious disease transmission in nature. Here we are concerned with the formulation of mathematical models that capture the essence of heterogeneity while keeping a simple structure suitable of analytical treatment. We explore the consequences of host heterogeneity in the susceptibility to infection for epidemiological models for which immunity conferred by infection is partially protective, known as susceptible-infected-recovered-infected (SIRI) models. We analyze the impact of heterogeneity on disease prevalence and contrast the susceptibility profiles of the subpopulations at risk for primary infection and reinfection. We present a systematic study in the case of two frailty groups.We predict that the average rate of reinfection may be higher than the average rate of primary infection, which may seem paradoxical given that primary infection induces life-long partial protection. Infection generates a selection mechanism whereby fit individuals remain in S and frail individuals are transferred to R. If this effect is strong enough we have a scenario where, on average, the rate of reinfection is higher than the rate of primary infection even though each individual has a risk reduction following primary infection. This mechanism may explain high rates of tuberculosis reinfection recently reported.Finally, the enhanced benefits of vaccination strategies that target the high-risk groups are quantified.     

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.     

A quantitative test of the relationship between parasite dose and infection probability across different host-parasite combinations

Epidemiological models generally assume that the number of susceptible individuals that become infected within a unit of time depends on the density of the hosts and the concentration of parasites (i.e. mass-action principle). However, empirical studies have found significant deviations from this assumption due to biotic and abiotic factors, such as seasonality, the spatial structure of the host population and host heterogeneity with respect to immunity and susceptibility. In this paper, we examine the effect of the dose level of the bacterial endoparasite Pasteuria ramosa on the infection rate of its host, the water flea Daphnia magna. Using seven host clones and two parasite isolates, we measure the fraction of infected hosts after exposure to eight different parasite doses to determine whether there is variation in the infection process across different host clone-parasite isolate combinations. In five combinations, a pronounced dose-dependent infection pattern was found. Using a likelihood approach, we compare the infection data of these five combinations to the fit of three mathematical models: a mass-action model, a parasite antagonism model (i.e. an increase in the parasite dose leads to an under-proportionate increase in the infection rate per host) and a heterogeneous host model. We found that the host heterogeneity model, in which we assumed the existence of non-inherited phenotypic differences in host susceptibilities to the parasite, provides the best fit. Our analysis suggests that among 5 out of the 14 host clone-parasite isolate combinations that resulted in appreciable infections, non-genetic host heterogeneity plays an important role.     

Dynamics of the Establishment of Systemic Potyvirus Infection: Independent yet Cumulative Action of Primary Infection Sites

In the clinic, farm, or field, for many viruses there is a high prevalence of mixed-genotype infections, indicating that multiple virions have initiated infection and that there can be multiple sites of primary infection within the same host. The dynamic process by which multiple primary infection sites interact with each other and the host is poorly understood, undoubtedly due to its high complexity. In this study, we attempted to unravel the basic interactions underlying this process using a plant RNA virus, as removing the inoculated leaf can instantly and rigorously eliminate all primary infection sites. Effective population size in the inoculated leaf and time of removal of the inoculated leaf were varied in experiments, and it was found that both factors positively influenced if the plant became systemically infected and what proportion of cells in the systemic tissue were infected, as measured by flow cytometry. Fitting of probabilistic models of infection to our data demonstrated that a null model in which the action of each focus is independent of the presence of other foci was better supported than a dependent-action model. The cumulative effect of independently acting foci therefore determined when plants became infected and how many individual cells were infected. There was no evidence for interference between primary infection sites, which is surprising given the planar structure of leaves. By showing that a simple null model is supported, we experimentally confirmed—to our knowledge for the first time—the minimal components that dictate interactions of a conspecific virus population establishing systemic infection.     

Host species,and not environment,predicts variation in blood parasite prevalence,distribution, and diversity along a humidity gradient in northern South America

Environmental factors strongly influence the ecology and evolution of vector‐borne infectious diseases. However, our understanding of the influence of climatic variation on host–parasite interactions in tropical systems is rudimentary. We studied five species of birds and their haemosporidian parasites (Plasmodium and Haemoproteus) at 16 sampling sites to understand how environmental heterogeneity influences patterns of parasite prevalence, distribution, and diversity across a marked gradient in water availability in northern South America. We used molecular methods to screen for parasite infections and to identify parasite lineages. To characterize spatial heterogeneity in water availability, we used weather‐station and remotely sensed climate data. We estimated parasite prevalence while accounting for spatial autocorrelation, and used a model selection approach to determine the effect of variables related to water availability and host species on prevalence. The prevalence, distribution, and lineage diversity of haemosporidian parasites varied among localities and host species, but we found no support for the hypothesis that the prevalence and diversity of parasites increase with increasing water availability. Host species and host × climate interactions had stronger effects on infection prevalence, and parasite lineages were strongly associated with particular host species. Because climatic variables had little effect on the overall prevalence and lineage diversity of haemosporidian parasites across study sites, our results suggest that independent host–parasite dynamics may influence patterns in parasitism in environmentally heterogeneous landscapes.     

One is enough: in vivo effective population size is dose-dependent for a plant RNA virus

Effective population size (N(e)) determines the strength of genetic drift and the frequency of co-infection by multiple genotypes, making it a key factor in viral evolution. Experimental estimates of N(e) for different plant viruses have, however, rendered diverging results. The independent action hypothesis (IAH) states that each virion has a probability of infection, and that virions act independent of one another during the infection process. A corollary of IAH is that N(e) must be dose dependent. A test of IAH for a plant virus has not been reported yet. Here we perform a test of an IAH infection model using a plant RNA virus, Tobacco etch virus (TEV) variants carrying GFP or mCherry fluorescent markers, in Nicotiana tabacum and Capsicum annuum plants. The number of primary infection foci increased linearly with dose, and was similar to a Poisson distribution. At high doses, primary infection foci containing both genotypes were found at a low frequency (<2%). The probability that a genotype that infected the inoculated leaf would systemically infect that plant was near 1, although in a few rare cases genotypes could be trapped in the inoculated leaf by being physically surrounded by the other genotype. The frequency of mixed-genotype infection could be predicted from the mean number of primary infection foci using the independent-action model. Independent action appears to hold for TEV, and N(e) is therefore dose-dependent for this plant RNA virus. The mean number of virions causing systemic infection can be very small, and approaches 1 at low doses. Dose-dependency in TEV suggests that comparison of N(e) estimates for different viruses are not very meaningful unless dose effects are taken into consideration.     

Genetic susceptibility to infectious disease: lessons from mouse models of leishmaniasis

Susceptibility to infectious disease is influenced by multiple host genes, most of which are low penetrance QTLs that are difficult to map in humans. Leishmaniasis is a well-studied infectious disease with a variety of symptoms and well-defined immunological features. Mouse models of this disease have revealed more than 20 QTLs as being susceptibility genes, studies of which have made important contributions to our understanding of the host response to infection. The functional effects of individual QTLs differ widely, indicating a networked regulation of these effects. Several of these QTLs probably also influence susceptibility to other infections, indicating that their characterization will contribute to our understanding of susceptibility to infectious disease in general.     

Meiotic recombination, cross-reactivity, and persistence in Plasmodium falciparum

We incorporate a representation of Plasmodium falciparum recombination within a discrete-event model of malaria transmission. We simulate the introduction of a new parasite genotype into a human population in which another genotype has reached equilibrium prevalence and compare the emergence and persistence of the novel recombinant forms under differing cross-reactivity relationships between the genotypes. Cross-reactivity between the parental (initial and introduced) genotypes reduces the frequency of appearance of recombinants within three years of introduction from 100% to 14%, and delays their appearance by more than a year, on average. Cross-reactivity between parental and recombinant genotypes reduces the frequency of appearance to 36% and increases the probability of recombinant extinction following appearance from 0% to 83%. When a recombinant is cross-reactive with its parental types, its probability of extinction is influenced by cross-reactivity between the parental types in the opposite manner; that is, its probability of extinction after appearance decreases. Frequencies of P. falciparum outcrossing are mediated by frequencies of mixed-genotype infections in the host population, which are in turn mediated by the structure of cross-reactivity between parasite genotypes. The three leading hypotheses about how meiosis relates to oocyst production lead to quantitative, but no qualitative, differences in these results.     

An experimental test of the independent action hypothesis in virus–insect pathosystems

The ‘independent action hypothesis’ (IAH) states that each pathogen individual has a non-zero probability of causing host death and that pathogen individuals act independently. IAH has not been rigorously tested. In this paper, we (i) develop a probabilistic framework for testing IAH and (ii) demonstrate that, in two out of the six virus–insect pathosystems tested, IAH is supported by the data. We first show that IAH inextricably links host survivorship to the number of infecting pathogen individuals, and develop a model to predict the frequency of single- and dual-genotype infections when a host is challenged with a mixture of two genotypes. Model predictions were tested using genetically marked, near-identical baculovirus genotypes, and insect larvae from three host species differing in susceptibility. Observations in early-instar larvae of two susceptible host species support IAH, but observations in late-instar larvae of susceptible host species and larvae of a less susceptible host species were not in agreement with IAH. Hence the model is experimentally supported only in pathosystems in which the host is highly susceptible. We provide, to our knowledge, the first qualitative experimental evidence that, in such pathosystems, the action of a single virion is sufficient to cause disease.     

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

Although heterogeneity in contact rate, physiology, and behavioral response to infection have all been empirically demonstrated in host–pathogen systems, little is known about how interactions between individual variation in behavior and physiology scale‐up to affect pathogen transmission at a population level. The objective of this study is to evaluate how covariation between the behavioral and physiological components of transmission might affect epidemic outcomes in host populations. We tested the consequences of contact rate covarying with susceptibility, infectiousness, and infection status using an individual‐based, dynamic network model where individuals initiate and terminate contacts with conspecifics based on their behavioral predispositions and their infection status. Our results suggest that both heterogeneity in physiology and subsequent covariation of physiology with contact rate could powerfully influence epidemic dynamics. Overall, we found that 1) individual variability in susceptibility and infectiousness can reduce the expected maximum prevalence and increase epidemic variability; 2) when contact rate and susceptibility or infectiousness negatively covary, it takes substantially longer for epidemics to spread throughout the population, and rates of epidemic spread remained suppressed even for highly transmissible pathogens; and 3) reductions in contact rate resulting from infection‐induced behavioral changes can prevent the pathogen from reaching most of the population. These effects were strongest for theoretical pathogens with lower transmissibility and for populations where the observed variation in contact rate was higher, suggesting that such heterogeneity may be most important for less infectious, more chronic diseases in wildlife. Understanding when and how variability in pathogen transmission should be modelled is a crucial next step for disease ecology.     

The effect of population heterogeneities upon spread of infection

It has often been observed that population heterogeneities can lead to outbreaks of infection being less frequent and less severe than homogeneous population models would suggest. We address this issue by comparing a model incorporating various forms of heterogeneity with a homogenised model matched according to the value of the basic reproduction number $R_0$ . We mainly focus upon heterogeneity in individuals’ infectivity and susceptibility, though with some allowance also for heterogeneous patterns of mixing. The measures of infectious spread we consider are (i) the probability of a major outbreak; (ii) the mean outbreak size; (iii) the mean endemic prevalence level; and (iv) the persistence time. For each measure, we establish conditions under which heterogeneity leads to a reduction in infectious spread. We also demonstrate that if such conditions are not satisfied, the reverse may occur. As well as comparison with a homogeneous population, we investigate comparisons between two heterogeneous populations of differing degrees of heterogeneity. All of our results are derived under the assumption that the susceptible population is sufficiently large.     

Maneuvering for advantage: the genetics of mouse susceptibility to virus infection

Genetic studies of host susceptibility to infection contribute to our understanding of an organism's response to pathogens at the immunological, cellular, and molecular levels. In this review we describe how the study of host genetics in mouse models has helped our understanding of host defense mechanisms against viral infection, and how this knowledge can be extended to human infections. We focus especially on the innate mechanisms that function as the host's first line of defense against infection. We also discuss the main issues that confront this field, as well as its future.     

The effect of host heterogeneity and parasite intragenomic interactions on parasite population structure

Understanding the processes that shape the genetic structure of parasite populations and the functional consequences of different parasite genotypes is critical for our ability to predict how an infection can spread through a host population and for the design of effective vaccines to combat infection and disease. Here, we examine how the genetic structure of parasite populations responds to host genetic heterogeneity. We consider the well-characterized molecular specificity of major histocompatibility complex binding of antigenic peptides to derive deterministic and stochastic models. We use these models to ask, firstly, what conditions favour the evolution of generalist parasite genotypes versus specialist parasite genotypes? Secondly, can parasite genotypes coexist in a population? We find that intragenomic interactions between parasite loci encoding antigenic peptides are pivotal in determining the outcome of evolution. Where parasite loci interact synergistically (i.e. the recognition of additional antigenic peptides has a disproportionately large effect on parasite fitness), generalist parasite genotypes are favoured. Where parasite loci act multiplicatively (have independent effects on fitness) or antagonistically (have diminishing effects on parasite fitness), specialist parasite genotypes are favoured. A key finding is that polymorphism is not stable and that, with respect to functionally important antigenic peptides, parasite populations are dominated by a single genotype.     

Multiple infections by the anther smut pathogen are frequent and involve related strains

Population models of host-parasite interactions predict that when different parasite genotypes compete within a host for limited resources, those that exploit the host faster will be selected, leading to an increase in parasite virulence. When parasites sharing a host are related, however, kin selection should lead to more cooperative host exploitation that may involve slower rates of parasite reproduction. Despite their potential importance, studies that assess the prevalence of multiple genotype infections in natural populations remain rare, and studies quantifying the relatedness of parasites occurring together as natural multiple infections are particularly scarce. We investigated multiple infections in natural populations of the systemic fungal plant parasite Microbotryum violaceum, the anther smut of Caryophyllaceae, on its host, Silene latifolia. We found that multiple infections can be extremely frequent, with different fungal genotypes found in different stems of single plants. Multiple infections involved parasite genotypes more closely related than would be expected based upon their genetic diversity or due to spatial substructuring within the parasite populations. Together with previous sequential inoculation experiments, our results suggest that M. violaceum actively excludes divergent competitors while tolerating closely related genotypes. Such an exclusion mechanism might explain why multiple infections were less frequent in populations with the highest genetic diversity, which is at odds with intuitive expectations. Thus, these results demonstrate that genetic diversity can influence the prevalence of multiple infections in nature, which will have important consequences for their optimal levels of virulence. Measuring the occurrence of multiple infections and the relatedness among parasites within hosts in natural populations may be important for understanding the evolutionary dynamics of disease, the consequences of vaccine use, and forces driving the population genetic structure of parasites.     

Role of MyD88 in route-dependent susceptibility to vesicular stomatitis virus infection

TLRs are important components of the innate immune response. The role of the TLR signaling pathway in host defense against a natural viral infection has been largely unexplored. We found that mice lacking MyD88, an essential adaptor protein in TLR signaling pathway, were extremely sensitive to intranasal infection with vesicular stomatitis virus, and this susceptibility was dose dependent. We demonstrated that this increased susceptibility correlates with the impaired production of IFN-alpha and defective induction and maintenance of neutralizing Ab. These studies outline the important role of the TLR signaling pathway in nasal mucosae-respiratory tracts-neuroepithelium environment in the protection against microbial pathogen infections. We believe that these results explain how the route of infection, probably by virtue of activating different cell populations, can lead to entirely different outcomes of infection based on the underlying genetics of the host.     

Immunity to intracellular pathogens as a complex genetic trait

Although the role of host heredity in susceptibility to infectious diseases is significant, the genetic control of immunity to infection remains poorly understood. Advances in experimental and epidemiological analyses of complex genetic traits have led to the discoveries of novel genetic determinants of host resistance. New loci that control susceptibility to a number of intracellular pathogens have been identified using mouse models of infectious diseases. The contributions of individual loci, however, vary in quantitative and qualitative manner, depending on mechanisms of pathogen virulence and genetic background of the host. In this review, we discuss how genetic analysis of host resistance contributes to further understanding of host immunity and pathogenesis of intracellular infections.     

Transmissible cancer in Tasmanian devils: localized lineage replacement and host population response

Tasmanian devil facial tumour disease (DFTD) is a clonally transmissible cancer threatening the Tasmanian devil (Sarcophilus harrisii) with extinction. Live cancer cells are the infectious agent, transmitted to new hosts when individuals bite each other. Over the 18 years since DFTD was first observed, distinct genetic and karyotypic sublineages have evolved. In this longitudinal study, we investigate the associations between tumour karyotype, epidemic patterns and host demographic response to the disease. Reduced host population effects and low DFTD infection rates were associated with high prevalence of tetraploid tumours. Subsequent replacement by a diploid variant of DFTD coincided with a rapid increase in disease prevalence, population decline and reduced mean age of the population. Our results suggest a role for tumour genetics in DFTD transmission dynamics and epidemic outcome. Future research, for this and other highly pathogenic emerging infectious diseases, should focus on understanding the evolution of host and pathogen genotypes, their effects on susceptibility and tolerance to infection, and their implications for designing novel genetic management strategies. This study provides evidence for a rapid localized lineage replacement occurring within a transmissible cancer epidemic and highlights the possibility that distinct DFTD genetic lineages may harbour traits that influence pathogen fitness.