The adaptive dynamics of the evolution of host resistance to indirectly transmitted microparasites

We use adaptive dynamics and pairwise invadability plots to examine the evolutionary dynamics of host resistance to microparasitic infection transmitted indirectly via free stages. We investigate trade-offs between pathogen transmission rate and intrinsic growth rate. Adaptive dynamics distinguishes various evolutionary outcomes associated with repellors, attractors or branching points. We find criteria corresponding to these and demonstrate that a major factor deciding the evolutionary outcome is whether trade-offs are acceleratingly or deceleratingly costly. We compare and contrast two models and show how the differences between them lead to different evolutionary outcomes.     

A baseline model for the apparent competition between many host strains: the evolution of host resistance to microparasites.

The purpose of this article is to establish and analyse a baseline model for the apparent competition between many host strains attempting to avoid a uniform microparasitic population. The model is formulated and analysed using invasion criteria in the main text. The results are verified by more formal methods in the appendix. Cases in which the microparasite can invade are distinguished geometrically from those in which it cannot using threshold and strain composition conditions. A major result obtained when the pathogen persists is a competitive exclusion principle for host resistance. For non-lethal infections, the winning strain is that which affords the pathogen maximum threshold density; for possibly lethal infections, a somewhat generalized version of this criterion is presented and discussed. The tension is highlighted between these results and the baseline behaviour of many pathogen strains and a uniform host population-here the winning pathogen strain is that with minimum threshold density.     

Community dynamics, trade-offs, invasion criteria and the evolution of host resistance to microparasites

A hybrid cellular automaton model is described and used to simulate early tumor growth and examine the roles of host tissue vascular density and tumor metabolism in the ability of a small number of monoclonal transformed cells to develop into an invasive tumor. The model incorporates normal cells, tumor cells, necrotic or empty space, and a random network of native microvessels as components of a cellular automaton state vector. Diffusion of glucose and H(+)ions (the latter largely resulting from the tumor's excessive reliance on anaerobic metabolism) to and from the microvessels, and their utilization or production by cells, is modeled through the solution of differential equations. In this way, the cells and microvessels affect the extracellular concentrations of glucose and H(+)which, in turn, affect the evolution of the automaton. Simulations of the model demonstrate that: (i) high tumor H(+)ion production is favorable for tumor growth and invasion; however for every H(+)ion production rate, there exists a range of optimal microvessel densities (leading to a local pH favorable to tumor but not to normal cells) for which growth and invasion is most effective, (ii) at vascular densities below this range, both tumor and normal cells die due to excessively low pH, (iii) for vascular densities above the optimal range the microvessel network is highly efficient at removing acid and therefore the tumor cells lose their advantage over normal cells gained by high local H(+)concentration. While significant spatial gradients of glucose formed, no regions of detrimentally poor glucose perfusion (for either cell type) were observed, regardless of microvessel density. Depending on metabolic phenotype, a variety of tumor morphologies similar to those clinically observed were realized in the simulations. Lastly, a sharp transition (analogous to that of the adenoma-carcinoma sequence) between states of initial tumor confinement and efficient invasiveness was observed when H(+)production reached a critical value.     

From host immunity to pathogen invasion: the effects of helminth coinfection on the dynamics of microparasites

Concurrent infections with multiple parasites are ubiquitous in nature. Coinfecting parasites can interact with one another in a variety of ways, including through the host's immune system via mechanisms such as immune trade-offs and immunosuppression. These within-host immune processes mediating interactions among parasites have been described in detail, but how they scale up to determine disease dynamic patterns at the population level is only beginning to be explored. In this review, we use helminth-microparasite coinfection as a model for examining how within-host immunological effects may influence the ecological outcome of microparasitic diseases, with a specific focus on disease invasion. The current literature on coinfection between helminths and major microparasitic diseases includes many studies documenting the effects of helminths on individual host responses to microparasites. In many cases, the observed host responses map directly onto parameters relevant for quantifying disease dynamics; however, there have been few attempts at integrating data on individual-level effects into theoretical models to extrapolate from the individual to the population level. Moreover, there is considerable variability in the particular combination of disease parameters affected by helminths across different microparasite systems. We develop a conceptual framework identifying some potential sources of such variability: Pathogen persistence and severity, and resource availability to hosts. We also generate testable hypotheses regarding diseases and the environmental contexts when the effects of helminths on microparasite dynamics should be most pronounced. Finally, we use a case study of helminth and mycobacterial coinfection in the African buffalo to illustrate both progress and challenges in understanding the population-level consequences of within-host immunological interactions, and conclude with suggestions for future research that will help improve our understanding of the effects of coinfection on dynamics of infectious diseases.     

The evolution of host resistance: tolerance and control as distinct strategies

In response to parasitic infection, hosts may evolve defences that reduce the deleterious effects on survivorship. This may be interpreted as a form of resistance, as long as infected hosts are able to either recover or reproduce. Here we distinguish two important routes to this form of resistance. An infected host may either: (1) tolerate pathogen damage, or (2) control the pathogen by inhibiting its growth. A model is constructed to examine the evolutionary dynamics of tolerance and control to a free-living microparasite, where both forms of resistance are costly in terms of other life-history traits. We do not observe polymorphism of tolerant genotypes. In contrast, the evolution of control may lead to disruptive selection, and ultimately dimorphism of extreme strains. The optimal host genotype also varies with the type of resistance-individuals invest more in tolerance and pay a greater cost. The free-living framework used makes the distinction between tolerance and control explicit but the distinction applies equally to directly transmitted parasites. Due to the evolutionary differences exhibited, it is important to design experiments that distinguish between the two forms of resistance.     

Evolution of microparasites in spatially and genetically structured host populations: The example of RHDV infecting rabbits

Several studies have shown that classical results of microparasite evolution could not extend to the case where the host species shows an important spatial structure. Rabbit haemorrhagic disease virus (RHDV), responsible for rabbit haemorrhagic disease (RHD), which recently emerged in rabbits, has strains within a wide range of virulence, thus providing an interesting example of competition between strains infecting a host species with a metapopulation structure. In addition, rabbits may show a genetic diversity regarding RHDV susceptibility. In the present paper we use the example of the rabbit-RHDV interaction to study the competition between strains of a same microparasite in a host population that is both spatially and genetically structured. Using metapopulation models we show that the evolution of the microparasite is guided by a trade-off between its capacity to invade subpopulations potentially infected by other strains and its capacity to persist within the subpopulation. In such a context, host genetic diversity acts by reducing the number of hosts susceptible to each strain, often favouring more persistent—and generally less virulent—strains. We also show that even in a stochastic context where host genes regularly go locally extinct, the microparasite pressure helps maintain the genetic diversity in the long term while reinforcing gene loss risk in the short term. Finally, we study how different demographic and epidemiologic parameters affect the coevolution between the rabbit and RHDV.     

The evolution of parasite virulence, superinfection, and host resistance

We analyze the evolutionary consequences of host resistance (the ability to decrease the probability of being infected by parasites) for the evolution of parasite virulence (the deleterious effect of a parasite on its host). When only single infections occur, host resistance does not affect the evolution of parasite virulence. However, when superinfections occur, resistance tends to decrease the evolutionarily stable (ES) level of parasite virulence. We first study a simple model in which the host does not coevolve with the parasite (i.e., the frequency of resistant hosts is independent of the parasite). We show that a higher proportion of resistant host decreases the ES level of parasite virulence. Higher levels of the efficiency of host resistance, however, do not always decrease the ES parasite virulence. The implications of these results for virulence management (evolutionary consequences of public health policies) are discussed. Second, we analyze the case where host resistance is allowed to coevolve with parasite virulence using the classical gene-for-gene (GFG) model of host-parasite interaction. It is shown that GFG coevolution leads to lower parasite virulence (in comparison with a fully susceptible host population). The model clarifies and relates the different components of the cost of parasitism: infectivity (ability to infect the host) and virulence (deleterious effect) in an evolutionary perspective.     

Exposure to host resistance mechanisms drives evolution of bacterial virulence in plants

Bacterial pathogenicity to plants and animals has evolved through an arms race of attack and defense. Key players are bacterial effector proteins, which are delivered through the type III secretion system and suppress basal defenses . In plants, varietal resistance to disease is based on recognition of effectors by the products of resistance (R) genes . When recognized, the effector or in this scenario, avirulence (Avr) protein triggers the hypersensitive resistance reaction (HR), which generates antimicrobial conditions . Unfortunately, such gene-for-gene-based resistance commonly fails because of the emergence of virulent strains of the pathogen that no longer trigger the HR . We have followed the emergence of a new virulent pathotype of the halo-blight pathogen Pseudomonas syringae pv. phaseolicola within leaves of a resistant variety of bean. Exposure to the HR led to the selection of strains lacking the avirulence (effector) gene avrPphB (or hopAR1), which triggers defense in varieties with the matching R3 resistance gene. Loss of avrPphB was through deletion of a 106 kb genomic island (PPHGI-1) that shares features with integrative and conjugative elements (ICElands) and also pathogenicity islands (PAIs) in diverse bacteria . We provide a molecular explanation of how exposure to resistance mechanisms in plants drives the evolution of new virulent forms of pathogens.     

Probability of resistance evolution for exponentially growing virus in the host

Chemotherapy for tumor and pathogenic virus often faces an emergence of resistant mutants, which may lead to medication failure. Here we study the risk of resistance to evolve in a virus population which grows exponentially. We assume that infected cells experience a "proliferation event" of virus at a random time and that the number of newly infected cells from an infected cell follows a Poisson distribution. Virus starts from a single infected cell and the virus infection is detected when the number of infected cells reaches a detection size. Initially virus is sensitive to a drug but later acquires resistance by mutations. We ask the probability that one or more cells infected with drug-resistant virus exist at the time of detection. We derive a formula for the probability of resistance and confirm its accuracy by direct computer simulations. The probability of resistance increases with detection size and mutation rate but decreases with the population growth rate of sensitive virus. The risk of resistance is smaller when more cells are newly infected by viral particles from a single infected cell if the viral growth rate is the same.     

The basic reproductive ratio of life

Template-directed polymerization of nucleotides is believed to be a pathway for the replication of genetic material in the earliest cells. We assume that activated monomers are produced by prebiotic chemistry. These monomers can undergo spontaneous polymerization, a system that we call “prelife.” Adding template-directed polymerization changes the equilibrium structure of prelife if the rate constants meet certain criteria. In particular, if the basic reproductive ratio of sequences of a certain length exceeds one, then those sequences can attain high abundance. Furthermore, if many sequences replicate, then the longest sequences can reach high abundance even if the basic reproductive ratios of all sequences are less than one. We call this phenomenon “subcritical life.” Subcritical life suggests that sequences long enough to be ribozymes can become abundant even if replication is relatively inefficient. Our work on the evolution of replication has interesting parallels to infection dynamics. Life (replication) can be seen as an infection of prelife.     

The effects of averaging on the basic reproduction ratio.

This paper formalizes the process of averaging the mixing patterns of behaviorally distinct individuals or groups. This averaging process is shown to decrease or leave unaltered the basic reproduction ratio R0 in epidemiological models with symmetric transmission between groups.     

Acquired immunity and stochasticity in epidemic intervals impede the evolution of host disease resistance

Disease can generate intense selection pressure on host populations, but here we show that acquired immunity in a population subject to repeated disease outbreaks can impede the evolution of genetic disease resistance by maintaining susceptible genotypes in the population. Interference between the life-history schedule of a species and periodicity of the disease has unintuitive effects on selection intensity, and stochasticity in outbreak period further reduces the rate of spread of disease-resistance alleles. A general age-structured population genetic model was developed and parameterized using empirical data for phocine distemper virus (PDV) epizootics in harbor seals. Scenarios with acquired immunity had lower levels of epizootic mortality compared with scenarios without acquired immunity for the first PDV outbreaks, but this pattern was reversed after about five disease cycles. Without acquired immunity, evolution of disease resistance was more rapid, and long-term population size variation is efficiently dampened. Acquired immunity has the potential to significantly influence rapid evolutionary dynamics of a host population in response to age-structured disease selection and to alter predicted selection intensities compared with epidemiological models that do not consider such feedback. This may have important implications for evolutionary population dynamics in a range of human, agricultural, and wildlife disease settings.     

The evolution of nettle resistance to heavy deer browsing

We examined whether heavy browsing by sika deer, Cervus nippon Temminck, changed morphological characteristics of a Japanese nettle, Urtica thunbergiana Sieb. et Zucc., in Nara Park, where a large population of sika deer has been maintained for more than 1,200 years. Wild nettles of Nara Park exhibited smaller leaf area, 11–223 times more stinging hairs per leaf, and 58–630-times higher stinging hair densities than those of other areas where there was no evidence of sika deer browsing. There were no significant differences in stinging hair length between the areas. Nettles from Nara Park that were cultivated from seeds in a greenhouse retained a larger number and higher density of stinging hairs. In the field, nettles of Nara Park were less frequently browsed by sika deer and showed higher survivorship than nettles that were transplanted from an unbrowsed area into Nara Park. These results indicate that: (1) the U. thunbergiana population of Nara Park has an extremely high stinging hair density compared with those of unbrowsed areas; (2) this characteristic has a genetic basis, and (3) stinging hairs serve as a defensive structure against sika deer, contributing to an increase in survivorship. Thus, we conclude that a U. thunbergiana population in Nara Park, with extremely high stinging hair densities, has evolved through natural selection due to heavy browsing by sika deer.     

The ecology and evolution of host-plant resistance to insects

Genetic techniques have yielded new insights into plant-herbivore coevolution. Quantitative genetic tests of herbivory theory reveal that in some cases insect herbivores impose selection on resistance traits. Also, some resistance traits are costly while others appear not to be, and genetic models can explain these results. Genetic variation in plant resistance influences insect community structure by modifying interactions of herbivores with competitors and natural enemies. Therefore, models of multispecies coevolution are more realistic than pairwise coevolutionary models. Ecological genetics will facilitate further theoretical and empirical exploration of multispecies coevolution of plants and herbivores.     

Parallel evolution of drug resistance in HIV: failure of nonsynonymous/synonymous substitution rate ratio to detect selection.

Parallel or convergent evolution at the molecular level has been difficult to demonstrate especially when rigorous statistical criteria are applied. We present sequence data from the protease gene from eight patients infected with the human immunodeficiency virus (HIV-1). These patients have been on multiple drug therapies for at least 2 years. We present sequence data from two timepoints: time zero--the initiation of drug therapy--and a subsequent timepoint between 59 and 104 weeks after the initiation of drug therapy. In addition to the sequence data, we present viral load data from both initial and final timepoints. Our phylogenetic analyses indicate significant evolution of virus from initial to final time points, even in three of eight patients who show low viral loads. Of the five patients who escaped drug therapy, identical amino acid replacements were seen in all five patients at two different codon positions, an indication of parallel evolution. We also measured genetic diversity for these patients and found no correlation between genetic diversity and viral load. Finally, we calculated the nonsynonymous and synonymous substitution rates and showed that the ratio of nonsynonymous to synonymous substitution compared to the value of one may be a poor indicator of natural selection.     

Host resistance to malaria: using mouse models to explore the host response

Malaria is a disease that infects over 500 million people, causing at least 1 million deaths every year, with the majority occurring in developing countries. The current antimalarial arsenal is becoming dulled due to the rapid rate of resistance of the parasite. However, in populations living in malaria-endemic regions there are many examples of genetic-based resistance to the severe effects of the parasite Plasmodium. Defining the genetic factors behind host resistance has been an area of great scientific interest over the last few decades; this review summarizes the current knowledge of the genetic loci involved. Perhaps the lessons learned from the natural variation in both the human populations and experimental mouse models of infection may pave the way for novel resistance-proof antimalarials.     

The evolution of parasite manipulation of host dispersal

We investigate the evolution of manipulation of host dispersal behaviour by parasites using spatially explicit individual-based simulations. We find that when dispersal is local, parasites always gain from increasing their hosts' dispersal rate, although the evolutionary outcome is determined by the costs-to-benefits ratio. However, when dispersal can be non-local, we show that parasites investing in an intermediate dispersal distance of their hosts are favoured even when the manipulation is not costly, due to the intrinsic spatial dynamics of the host-parasite interaction. Our analysis highlights the crucial importance of ecological spatial dynamics in evolutionary processes and reveals the theoretical possibility that parasites could manipulate their hosts' dispersal.     

害虫抗药性的显性水平与抗性进化

对杀虫剂的代谢抗性和主要靶标抗性的显性水平作了理论解释,其中包括昆虫对Bt抗性的显性水平的解释。并对抗性显性具有的多变性作了阐述。分析抗性显性水平与抗药性进化的关系,认为在抗性进化早期抗性表现为显性的基因频率上升快于抗性表现为隐性时;但在抗性等位基因频率较高且出现抗性纯合子个体时,抗性表现为隐性的基因频率上升显著快于抗性表现为显性时。最后论述抗性显性在抗性治理中的应用。