A mathematical model for a new mechanism of phenotypic variation in malaria

Dissecting the determinants of malaria chronicity: why within-host models struggle to reproduce infection dynamics

The duration of infection is fundamental to the epidemiological behaviour of any infectious disease, but remains one of the most poorly understood aspects of malaria. In endemic areas, the malaria parasite Plasmodium falciparum can cause both acute, severe infections and asymptomatic, chronic infections through its interaction with the host immune system. Frequent superinfection and massive parasite genetic diversity make it extremely difficult to accurately measure the distribution of infection lengths, complicating the estimation of basic epidemiological parameters and the prediction of the impact of interventions. Mathematical models have qualitatively reproduced parasite dynamics early during infection, but reproducing long-lived chronic infections remains much more challenging. Here, we construct a model of infection dynamics to examine the consequences of common biological assumptions for the generation of chronicity and the impact of co-infection. We find that although a combination of host and parasite heterogeneities are capable of generating chronic infections, they do so only under restricted parameter choices. Furthermore, under biologically plausible assumptions, co-infection of parasite genotypes can alter the course of infection of both the resident and co-infecting strain in complex non-intuitive ways. We outline the most important puzzles for within-host models of malaria arising from our analysis, and their implications for malaria epidemiology and control.

The dynamics of naturally acquired immunity to Plasmodium falciparum infection

Severe malaria occurs predominantly in young children and immunity to clinical disease is associated with cumulative exposure in holoendemic settings. The relative contribution of immunity against various stages of the parasite life cycle that results in controlling infection and limiting disease is not well understood. Here we analyse the dynamics of Plasmodium falciparum malaria infection after treatment in a cohort of 197 healthy study participants of different ages in order to model naturally acquired immunity. We find that both delayed time-to-infection and reductions in asymptomatic parasitaemias in older age groups can be explained by immunity that reduces the growth of blood stage as opposed to liver stage parasites. We found that this mechanism would require at least two components – a rapidly acting strain-specific component, as well as a slowly acquired cross-reactive or general immunity to all strains. Analysis and modelling of malaria infection dynamics and naturally acquired immunity with age provides important insights into what mechanisms of immune control may be harnessed by malaria vaccine strategists.

Human malaria infections resulting in serious complications and death occur predominantly in young children, and resistance is gradually acquired with repeated exposure. Malaria parasites have two major stages within the human host during its life cycle: an initial liver stage, and the subsequent blood stage, where parasites replicate in and destroy red blood cells. The mechanisms of acquired resistance to severe malaria may involve immunity to both the liver and blood stage parasites. However the relative contribution of each type of immunity is not yet understood. To gain novel insight, we have analysed data from a malaria exposed cohort from western Kenya. We used mathematical modeling to understand what form of immunity is consistent with the observed rates of reinfection in adults and children seen in the field study data. We found that the reinfection pattern can be completely explained by blood stage immunity. Moreover, the blood stage immunity must consist of rapidly-induced strain-specific immunity that clears individual infections, and general immunity that accumulates slowly and decreases the average parasite growth rate with age. Understanding the dynamics of naturally acquired immunity and infection provides important insights for effective vaccine development.

Evolution of the multi-domain structures of virulence genes in the human malaria parasite, Plasmodium falciparum

The var gene family of Plasmodium falciparum encodes the immunodominant variant surface antigens PfEMP1. These highly polymorphic proteins are important virulence factors that mediate cytoadhesion to a variety of host tissues, causing sequestration of parasitized red blood cells in vital organs, including the brain or placenta. Acquisition of variant-specific antibodies correlates with protection against severe malarial infections; however, understanding the relationship between gene expression and infection outcome is complicated by the modular genetic architectures of var genes that encode varying numbers of antigenic domains with differential binding specificities. By analyzing the domain architectures of fully sequenced var gene repertoires we reveal a significant, non-random association between the number of domains comprising a var gene and their sequence conservation. As such, var genes can be grouped into those that are short and diverse and genes that are long and conserved, suggesting gene length as an important characteristic in the classification of var genes. We then use an evolutionary framework to demonstrate how the same evolutionary forces acting on the level of an individual gene may have also shaped the parasite's gene repertoire. The observed associations between sequence conservation, gene architecture and repertoire structure can thus be explained by a trade-off between optimizing within-host fitness and minimizing between-host immune selection pressure. Our results demonstrate how simple evolutionary mechanisms can explain var gene structuring on multiple levels and have important implications for understanding the multifaceted epidemiology of P. falciparum malaria.

Plasmodium falciparum, the most severe of the human malarias, contains within its genome a family of ∼60 var genes which play an important role in disease pathology and maintenance of chronic infections. Var genes have a modular genetic architecture and encode varying numbers of binding domains with specific preferences to a range of host tissues. Given the availability of host receptors for binding and the immunogenic properties of each domain it is not clear why genes encode multiple domains at once and how these are structured within each parasite's antigenic repertoire. Here we investigate the domain architecture of these important virulence genes and highlight an evolutionary trade-off between maintaining within-host fitness and optimizing between-host transmission success as an important driver in structuring var genes and var gene repertoires alike.

Problems with continuous-time malaria models in describing gametocytogenesis

Most mathematical models of malaria infection represent parasites as replicating continuously at a constant rate whereas in reality, malaria parasites replicate at a fixed age. The behaviour of continuous-time models when gametocytogenesis is included, in comparison to a more realistic discrete-time model that incorporates a fixed replication age was evaluated. Both the infection dynamics under gametocytogenesis and implications for predicting the amount parasites should invest into gametocytes (level of investment favoured by natural selection) are considered. It is shown that the many malaria models with constant replication rates can be represented by just 3 basic types. For these 3 types, it is then shown that under gametocytogenesis (i) in 2 cases, parasite multiplication and gametocyte production is mostly much too low, (ii) in the third, parasite multiplication and gametocyte production is mostly much too high, (iii) the effect of gametocyte investment on parasite multiplication is mostly too high, (iv) the effect of gametocyte investment on gametocyte production is nearly always too low and (v) with a simple approximation of fitness, the predicted level of gametocyte investment is mostly much too low. However, a continuous model with 48 age-compartments compares well to the discrete model. These findings are a further argument for modelling malaria infections in discrete time.