Abstract
Plasmodium falciparum, the most virulent human malaria parasite, undergoes asexual reproduction within the human host, but reproduces sexually within its vector host, the Anopheles mosquito. Consequently, the mosquito stage of the parasite life cycle provides an opportunity to create genetically novel parasites in multiply-infected mosquitoes, potentially increasing parasite population diversity. Despite the important implications for disease transmission and malaria control, a quantitative mapping of how parasite diversity entering a mosquito relates to diversity of the parasite exiting, has not been undertaken. To examine the role that vector biology plays in modulating parasite diversity, we develop a two-part model framework that estimates the diversity as a consequence of different bottlenecks and expansion events occurring during the vector-stage of the parasite life cycle. For the underlying framework, we develop the first stochastic model of within-vector P. falciparum parasite dynamics and go on to simulate the dynamics of two parasite subpopulations, emulating multiply infected mosquitoes. We show that incorporating stochasticity is essential to capture the extensive variation in parasite dynamics, particularly in the presence of multiple parasites. In particular, unlike deterministic models, which always predict the most fit parasites to produce the most sporozoites, we find that occasionally only parasites with lower fitness survive to the sporozoite stage. This has important implications for onward transmission. The second part of our framework includes a model of sequence diversity generation resulting from recombination and reassortment between parasites within a mosquito. Our two-part model framework shows that bottlenecks entering the oocyst stage decrease parasite diversity from what is present in the initial gametocyte population in a mosquito’s blood meal. However, diversity increases with the possibility for recombination and proliferation in the formation of sporozoites. Furthermore, when we begin with two parasite subpopulations in the initial gametocyte population, the probability of transmitting more than two unique parasites from mosquito to human is over 50% for a wide range of initial gametocyte densities.
Document Type
Article
Publication Date
5-22-2017
Digital Object Identifier (DOI)
https://doi.org/10.1371/journal.pone.0177941
Funding Information
L.M.C. was supported by award number U54GM088558 from the National Institute of General Medical Sciences. The authors also acknowledge the support of Virginia Tech’s Open Access Subvention Fund.
Repository Citation
Childs, Lauren M. and Prosper, Olivia F., "Simulating Within-Vector Generation of the Malaria Parasite Diversity" (2017). Mathematics Faculty Publications. 22.
https://uknowledge.uky.edu/math_facpub/22
S1 Fig. Diagram of the underlying within-vector parasite dynamics model.
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S2 Fig. Diagram of the within-vector parasite diversity generation model.
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S3 Fig. Oocyst and sporozoite prevalence versus initial gametocyte number.
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S4 Fig. Cumulative formed and ruptured oocysts with step function.
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S5 Fig. Comparison of cumulative rupture counts for continuous and step rupture functions.
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S6 Fig. Comparison of rupture time frequencies for continuous and step rupture functions.
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S7 Fig. Composition of nucleotide diversity.
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S8 Fig. Nucleotide diversity comparison between oocysts and sporozoites.
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S9 Fig. Number of unique sequences with the deterministic model.
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S10 Fig. Nucleotide diversity with the deterministic model.
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S1 Appendix. Description of simulation method and diversity generation protocol.
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S1 File. MATLAB code for life-cycle model.
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S2 File. MATLAB code for diversity model.
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S1 Table. Two-parasite population CTMC transition matrix.
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S2 Table. Oocyst prevalence and intensity summary statistics.
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S3 Table. Position of barcode SNPs.
Notes/Citation Information
Published in PLOS ONE, v. 12, 5, e0177941, p. 1-23.
© 2017 Childs, Prosper.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.