Accounting for red blood cell accessibility reveals distinct invasion strategies in Plasmodium falciparum strains

Francisco Y. Cai, Tiffany M. DeSimone, Elsa Hansen, Cameron V. Jennings, Amy K. Bei, Ambroise D. Ahouidi, Souleymane Mboup, Manoj T. Duraisingh, Caroline O. Buckee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


The growth of the malaria parasite Plasmodium falciparum in human blood causes all the symptoms of malaria. To proliferate, non-motile parasites must have access to susceptible red blood cells, which they invade using pairs of parasite ligands and host receptors that define invasion pathways. Parasites can switch invasion pathways, and while this flexibility is thought to facilitate immune evasion, it may also reflect the heterogeneity of red blood cell surfaces within and between hosts. Host genetic background affects red blood cell structure, for example, and red blood cells also undergo dramatic changes in morphology and receptor density as they age. The in vivo consequences of both the accessibility of susceptible cells, and their heterogeneous susceptibility, remain unclear. Here, we measured invasion of laboratory strains of P. falciparum relying on distinct invasion pathways into red blood cells of different ages. We estimated invasion efficiency while accounting for red blood cell accessibility to parasites. This approach revealed different tradeoffs made by parasite strains between the fraction of cells they can invade and their invasion rate into them, and we distinguish “specialist” strains from “generalist” strains in this context. We developed a mathematical model to show that generalist strains would lead to higher peak parasitemias in vivo compared to specialist strains with similar overall proliferation rates. Thus, the ecology of red blood cells may play a key role in determining the rate of P. falciparum parasite proliferation and malaria virulence.

Original languageEnglish (US)
Article numbere1007702
JournalPLoS computational biology
Issue number4
StatePublished - Apr 2020

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics


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