Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 May 6;5(5):e10444.
doi: 10.1371/journal.pone.0010444.

On the control of acute rodent malaria infections by innate immunity

Affiliations

On the control of acute rodent malaria infections by innate immunity

Beth F Kochin et al. PLoS One. .

Abstract

Does specific immunity, innate immunity or resource (red blood cell) limitation control the first peak of the blood-stage parasite in acute rodent malaria infections? Since mice deficient in specific immunity exhibit similar initial dynamics as wild-type mice it is generally viewed that the initial control of parasite is due to either limitation of resources (RBC) or innate immune responses. There are conflicting views on the roles of these two mechanisms as there is experimental evidence supporting both these hypotheses. While mathematical models based on RBC limitation are capable of describing the dynamics of primary infections, it was not clear whether a model incorporating the key features of innate immunity would be able to do the same. We examine the conditions under which a model incorporating parasite and innate immunity can describe data from acute Plasmodium chabaudi infections in mice. We find that innate immune response must decay slowly if the parasite density is to fall rather than equilibrate. Further, we show that within this framework the differences in the dynamics of two parasite strains are best ascribed to differences in susceptibility to innate immunity, rather than differences in the strains' growth rates or their propensity to elicit innate immunity. We suggest that further work is required to determine if innate immunity or resource limitation control acute malaria infections in mice.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Schematic of model.
In our model the density of the parasite, formula image, depends on two factors – its own replication (at rate formula image) and its clearance by activated innate immune cells formula image at rate formula image. The total number of innate immune cells equals formula image and they can be either in a resting or activated state. Since formula image is the number of activated cells, the number of resting cells equals formula image. Resting innate immune cells are activated at rate formula image, and revert back to the inactive state at exponential rate formula image.
Figure 2
Figure 2. Experimental data and models for the dynamics of strains AS (red dashed lines) and AJ (blue solid lines).
We use the model described in the text to investigate whether the dynamics of AS and AJ could be explained by (I) AJ having a higher growth rate than AS; (II) AJ inducing innate immunity more slowly than AS; or (III) AJ being less susceptible to killing by innate immunity than AS. Host Parameters: formula image (that is, no innate immunity is activated at infection), formula image dayformula image and formula image. Strain parameters are estimated using the single infection data from days 2–10 only (unshaded area). Strain parameters, I: formula image cells, formula image dayformula image, formula image dayformula image, formula image daysformula imagecellsformula image, formula image dayformula image. II: formula image cells, formula image dayformula image, formula image daysformula imagecellsformula image, formula image daysformula imagecellsformula image, formula image. III: formula image cells, formula image dayformula image, formula image daysformula imagecellsformula image, formula image dayformula image, formula image dayformula image. The left-hand column shows the mean parasite counts over time from experimental data for single infections (panel a; n = 11 (AJ) and n = 14 (AS)) and co-infections (panels e, i, m; n = 4, 4 and 5 respectively).

Similar articles

Cited by

References

    1. Roberts D, Craig A, Berendt A, Pinches R, Nash G, et al. Rapid switching to multiple antigenic and adhesive phenotypes in malaria. Nature. 1992;357:689–692. - PMC - PubMed
    1. Borst P, Bitter W, McCulloch R, Van Leeuwen F, Rudenko G. Antigenic variation in malaria. Cell. 1995;82:1–4. - PubMed
    1. Molineaux L, Diebner HH, Eichner M, Collins WE, Jeffery GM, et al. Plasmodium falciparum parasitaemia described by a new mathematical model. Parasitology. 2001;122:379–91. - PubMed
    1. Paget-McNicol S, Gatton M, Hastings I, Saul A. The Plasmodium falciparum var gene switching rate, switching mechanism and patterns of parasite recrudescence described by mathematical modelling. Parasitology. 2002;124:225–35. - PubMed
    1. Recker M, Nee S, Bull PC, Kinyanjui S, Marsh K, et al. Transient cross-reactive immune responses can orchestrate antigenic variation in malaria. Nature. 2004;429:555–8. - PubMed

Publication types