Evolution of virulence in opportunistic pathogens: generalism, plasticity, and control

Standard virulence evolution theory assumes that virulence factors are maintained because they aid parasitic exploitation, increasing growth within and/or transmission between hosts. An increasing number of studies now demonstrate that many opportunistic pathogens (OPs) do not conform to these assumptions, with virulence factors maintained instead because of advantages in non-parasitic contexts. Here we review virulence evolution theory in the context of OPs and highlight the importance of incorporating environments outside a focal virulence site. We illustrate that virulence selection is constrained by correlations between these external and focal settings and pinpoint drivers of key environmental correlations, with a focus on generalist strategies and phenotypic plasticity. We end with a summary of key theoretical and empirical challenges to be met for a fuller understanding of OPs

Malaria parasites prepare for flight

Life in seasonal environments often means facing extreme environmental fluctuations. Many multicellular organisms have evolved strategies to cope with this lifestyle. Single-celled malaria parasites are no different. An elegant experiment reveals that they respond to the availability of mosquitoes to make the most of seasonal transmission opportunities

Pathogen evolution in switching environments: a hybrid dynamical system approach

We propose a hybrid dynamical system approach to model the evolution of a pathogen that experiences different selective pressures according to a stochastic process. In every environment, the evolution of the pathogen is described by a version of the Fisher-Haldane-Wright equation while the switching between environments follows a Markov jump process. We investigate how the qualitative behavior of a simple single-host deterministic system changes when the stochastic switching process is added. In particular, we study the stability in probability of monomorphic equilibria. We prove that in a "constantly" fluctuating environment, the genotype with the highest mean fitness is asymptotically stable in probability. However, if the probability of host switching depends on the genotype composition of the population, polymorphism can be stably maintained. This is a corrected version of the paper that appeared in Mathematical Biosciences 240 (2012), p. 70-75. A corrigendum has appeared in the same journal.Comment: 15 pages, 4 figure

The Problem of Auto-Correlation in Parasitology

Explaining the contribution of host and pathogen factors in driving infection dynamics is a major ambition in parasitology. There is increasing recognition that analyses based on single summary measures of an infection (e.g., peak parasitaemia) do not adequately capture infection dynamics and so, the appropriate use of statistical techniques to analyse dynamics is necessary to understand infections and, ultimately, control parasites. However, the complexities of within-host environments mean that tracking and analysing pathogen dynamics within infections and among hosts poses considerable statistical challenges. Simple statistical models make assumptions that will rarely be satisfied in data collected on host and parasite parameters. In particular, model residuals (unexplained variance in the data) should not be correlated in time or space. Here we demonstrate how failure to account for such correlations can result in incorrect biological inference from statistical analysis. We then show how mixed effects models can be used as a powerful tool to analyse such repeated measures data in the hope that this will encourage better statistical practices in parasitology

Limited impact of within-vector ecology on the evolution of malaria parasite transmission investment

Malaria parasites spend part of their life in a vertebrate host and the rest in an arthropod vector and must successfully navigate both environments to gain fitness. In vertebrate hosts, malaria parasites infect red blood cells and can either replicate asexually or develop into the sexual form required for transmission to the vector. Despite the clear fitness benefits of onward transmission, only a small proportion of malaria parasites convert to sexual development. Mathematical models seeking to test the plausibility of various hypotheses to explain these low “conversion rates” have focused almost exclusively on the vertebrate/host half of the parasite life cycle. Here, we examined how processes occurring in the vector, including density-dependent parasite development and parasite-induced vector mortality, influence the evolution of parasite conversion rate in the host by developing a multi-scale model of within-host infection dynamics and parasite within-vector developmental processes for rodent malaria. We found that, regardless of model specifications (e.g., definitions of fitness, magnitude of parasite-induced vector mortality), considering processes within the vector had only a weak influence on the optimal conversion rate, but substantially diminished the fitness returns for all strategies and resulted in a sharper declines off the optima. Our approach allowed us to derive new metrics of parasite fitness (which we call “infectivity functions”) that link within-host gametocyte density to the probability of transmission to new hosts after passing through the vector, and that prevent overestimation of parasite transmission potential

Opportunities and challenges of Integral Projection Models for modelling host-parasite dynamics

Summary Epidemiological dynamics are shaped by and may in turn shape host demography. These feedbacks can result in hard to predict patterns of disease incidence. Mathematical models that integrate infection and demography are consequently a key tool for informing expectations for disease burden and identifying effective measures for control. A major challenge is capturing the details of infection within individuals and quantifying their downstream impacts to understand population-scale outcomes. For example, parasite loads and antibody titres may vary over the course of an infection and contribute to differences in transmission at the scale of the population. To date, to capture these subtleties, models have mostly relied on complex mechanistic frameworks, discrete categorization and/or agent-based approaches. Integral Projection Models (IPMs) allow variance in individual trajectories of quantitative traits and their population-level outcomes to be captured in ways that directly reflect statistical models of trait–fate relationships. Given increasing data availability, and advances in modelling, there is considerable potential for extending this framework to traits of relevance for infectious disease dynamics. Here, we provide an overview of host and parasite natural history contexts where IPMs could strengthen inference of population dynamics, with examples of host species ranging from mice to sheep to humans, and parasites ranging from viruses to worms. We discuss models of both parasite and host traits, provide two case studies and conclude by reviewing potential for both ecological and evolutionary research

Immune-mediated competition in rodent malaria is most likely caused by induced changes in innate immune clearance of merozoites

Malarial infections are often genetically diverse, leading to competitive interactions between parasites. A quantitative understanding of the competition between strains is essential to understand a wide range of issues, including the evolution of virulence and drug resistance. In this study, we use dynamical-model based Bayesian inference to investigate the cause of competitive suppression of an avirulent clone of Plasmodium chabaudi (AS) by a virulent clone (AJ) in immuno-deficient and competent mice. We test whether competitive suppression is caused by clone-specific differences in one or more of the following processes: adaptive immune clearance of merozoites and parasitised red blood cells (RBCs), background loss of merozoites and parasitised RBCs, RBC age preference, RBC infection rate, burst size, and within-RBC interference. These processes were parameterised in dynamical mathematical models and fitted to experimental data. We found that just one parameter μ, the ratio of background loss rate of merozoites to invasion rate of mature RBCs, needed to be clone-specific to predict the data. Interestingly, μ was found to be the same for both clones in single-clone infections, but different between the clones in mixed infections. The size of this difference was largest in immuno-competent mice and smallest in immuno-deficient mice. This explains why competitive suppression was alleviated in immuno-deficient mice. We found that competitive suppression acts early in infection, even before the day of peak parasitaemia. These results lead us to argue that the innate immune response clearing merozoites is the most likely, but not necessarily the only, mediator of competitive interactions between virulent and avirulent clones. Moreover, in mixed infections we predict there to be an interaction between the clones and the innate immune response which induces changes in the strength of its clearance of merozoites. What this interaction is unknown, but future refinement of the model, challenged with other datasets, may lead to its discovery

Facilitation through altered resource availability in a mixed-species rodent malaria infection

A major challenge in disease ecology is to understand how co‐infecting parasite species interact. We manipulate in vivo resources and immunity to explain interactions between two rodent malaria parasites, Plasmodium chabaudi and P. yoelii. These species have analogous resource‐use strategies to the human parasites Plasmodium falciparum and P. vivax: P. chabaudi and P. falciparum infect red blood cells (RBC) of all ages (RBC generalist); P. yoelii and P. vivax preferentially infect young RBCs (RBC specialist). We find that: (1) recent infection with the RBC generalist facilitates the RBC specialist (P. yoelii density is enhanced ~10 fold). This occurs because the RBC generalist increases availability of the RBC specialist's preferred resource; (2) co‐infections with the RBC generalist and RBC specialist are highly virulent; (3) and the presence of an RBC generalist in a host population can increase the prevalence of an RBC specialist. Thus, we show that resources shape how parasite species interact and have epidemiological consequences