Quantifying the removal of red blood cells in Macaca mulatta during a Plasmodium coatneyi infection

Abstract

Background: Malaria is the most deadly parasitic disease in humans globally, and the long-time coexistence with malaria has left indelible marks in the human genome that are the causes of a variety of genetic disorders. Although anaemia is a common clinical complication of malaria, the root causes and mechanisms involved in the pathogenesis of malarial anaemia are unclear and difficult to study in humans. Non-human primate (NHP) model systems enable the mechanistic study and quantification of underlying causative factors of malarial anaemia, and particularly the onset of severe anaemia.

Methods: Data were obtained in the course of Plasmodium coatneyi infections of malaria-naïve and semi-immune rhesus macaques (Macaca mulatta), whose red blood cells (RBCs) were labelled in situ with biotin at the time the infections were initiated. The data were used for a survival analysis that permitted, for the first time, an accurate estimation of the lifespan of erythrocytes in macaques. The data furthermore formed the basis for the development and parameterization of a recursive dynamic model of erythrocyte turnover, which was used for the quantification of RBC production and removal in each macaque.

Results: The computational analysis demonstrated that the lifespan of erythrocytes in macaques is 98 ± 21 days. The model also unambiguously showed that death due to senescence and parasitaemia is not sufficient to account for the extent of infection-induced anaemia. Specifically, the model permits, for the first time, the quantification of the different causes of RBC death, namely, normal senescence, age-independent random loss, parasitization, and bystander effects in uninfected cells. Such a dissection of the overall RBC removal process is hardly possible with experimental means alone. In the infected malaria-naïve macaques, death of erythrocytes by normal physiological senescence processes accounts for 20 % and parasitization for only 4 %, whereas bystander effects are associated with an astonishing 76 % of total RBC losses. Model-based comparisons of alternative mechanisms involved in the bystander effect revealed that most of the losses are likely due to a process of removing uninfected RBCs of all age classes and only minimally due to an increased rate of senescence of the uninfected RBCs.

Conclusions: A new malaria blood-stage model was developed for the analysis of data characterizing P. coatneyi infections of M. mulatta. The model used a discrete and recursive framework with age-structure that allowed the quantification of the most significant pathophysiological processes of RBC removal. The computational results revealed that the malarial anaemia caused by this parasite is mostly due to a loss of uninfected RBCs by an age-independent process. The biological identity and complete mechanism of this process is not fully understood and requires further investigation.

Keywords: Macaca mulatta; Malarial anaemia; Mathematical model; Plasmodium coatneyi; Red blood cell removal.

Fig. 1

Experimental results redrawn from Moreno et al. [14]. These results were used for the quantification of the RBC production and removal processes. Data points represent the means of five rhesus macaques. The parasite levels in the naïve infected group (bottom panel) become undetectable after sub-curative treatment on day 10

Fig. 2

Model scheme of RBC turnover. Two pools of RBCs are modelled, namely RBC (unlabelled RBCs) and bRBC (biotinylated RBCs), the sum of which equals the total number of RBCs and is proportional to the total amount of haemoglobin present. Production of RBCs by erythropoiesis only increases the unlabelled RBC pool (RBC). Both pools of RBCs (RBC + bRBC) are prone to removal by four processes: age-dependent death (senescence), age-independent (random) death, removal of uninfected RBCs (uRemoval), and removal due to parasitization. Parasitization occurs when a merozoite (M) infects a RBC, thus becoming an infected RBC (iRBC). Infected RBCs stimulate an immune-response (I), which in turn leads to the removal of infected RBCs. At the start of a simulation, all RBCs are biotinylated. All pools of RBCs have age-classes, which are not depicted in the scheme for simplicity. Unlabelled and biotinylated RBCs have 3840 age-classes, whereas infected RBCs have only 48 age-classes

Fig. 3

Determination of the hazard function for RBCs in healthy rhesus macaques. The left panel shows the experimentally determined time courses of biotinylated RBC survival for five healthy rhesus macaques (dots). The red line depicts the best fit time course for the biotinylated RBCs survival, which was obtained from the hazard function (green) in the panel on the right. This panel also exhibits the corresponding survival curve (blue) and the associated probability density function (red). From the probability density function, an average RBC lifespan of 98 ± 21 days was calculated

Fig. 4

Comparison of the average levels of RBC production and removal calculated for malaria naïve infected, semi-immune infected, and control rhesus macaques. The plot shows the total amount of production and removal by the different processes affecting RBCs during the 30-day period when the macaques were followed. In the infected macaques, the production was separated into two components: the amount of erythropoietic output the macaques would have had if they had not been infected (Non-infected Production) and the production of RBCs induced by the infection. Four different removal processes were quantified, two of which are normal physiological processes: Senescence Removal and Age-independent Removal. Here, age-independent removal accounts for the normal lysis of RBCs, which occurs in circulation due to the physical stresses imposed on the RBCs, but which are not dependent on age. Senescence removal accounts for all normal processes by which RBCs are taken from circulation due to age. The two removal processes that are due to the infection with Plasmodium are direct removal due to parasitization and removal of uninfected RBCs. The former includes only cells that are infected by the parasite, whereas the latter accounts for RBCs that are removed during an infection but were not infected by a merozoite

Fig. 5

Comparison of time-courses of the inferred erythropoietic output and experimental reticulocytes. The red lines represent the average erythropoietic outputs determined for each of the macaques, while the blue dots indicate the average of measured reticulocyte levels for each designated experimental group: a malaria naïve infected, b semi-immune infected, and c control macaques

Fig. 6

Model simulations comparing cases of no infection, infection alone, and infection with removal of uninfected RBCs and up-regulation of erythropoiesis. Simulation of a healthy, non-infected macaque is shown as a blue line. In a healthy macaque, biotinylated RBCs are only slowly lost due to senescence and age-independent processes, while erythropoiesis compensates the loss by producing unlabelled RBCs in such a way that no significant change in haemoglobin is seen. Simulation of an infected macaque, without taking into account loss of uninfected RBCs, is shown as a red line. Relative to the healthy macaque, only a small number of biotinylated and unlabelled RBCs are removed by parasitization (mainly at around days 8–10) and infected RBCs are produced. These results do not match the experimental results (circles) for haemoglobin and biotinylated RBCs. However, if an infected macaque is simulated taking into account loss of uninfected RBCs and up-regulation of erythropoiesis green line, then these processes can be estimated such that the model captures the behavior of the experimental data (circles) obtained for that particular animal

Fig. 7

Comparison of fits and predictions of the two mechanistic hypotheses regarding the removal of uninfected RBCs, namely the age-independent model and the increased senescence model. a The time course of biotinylated RBCs predicted by each model (blue line age-independent model and red line increased senescence model), superimposed on the experimental results (circles) by Moreno et al. [14]. b Exhibits the time courses of the median ages of the RBC populations, predicted by each model (blue line age-independent model and red line increased rate of senescence model). The shaded areas highlight the 25th and 75th percentiles of the age distributions of each RBC population. The light gray line highlights the time course of parasitaemia, and the dark grey line exhibits the time course for the erythropoietic output as predicted for the age-independent model. c The haemoglobin time courses predicted by each model (blue line age-independent model and red line increased senescence model), along with experimental results (circles) by Moreno et al. [14]. d Exhibits the age-distributions of RBC populations for the age-independent model (blue line) and for the increased senescence model (red line) at day 9, which corresponds to the highest parasitaemia level (see panel b). For comparisons, the age-distribution of a healthy RBC population (green line) which corresponds to the initial state (day 0) of both models, is also shown