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A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta

BACKGROUND: Plasmodium vivax can cause severe malaria. The total parasite biomass during infections is correlated with the severity of disease but not necessarily quantified accurately by microscopy. This finding has raised the question whether there could be sub-populations of parasites that are no...

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Autores principales: Fonseca, Luis L., Joyner, Chester J., Galinski, Mary R., Voit, Eberhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608162/
https://www.ncbi.nlm.nih.gov/pubmed/28923058
http://dx.doi.org/10.1186/s12936-017-2008-4
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author Fonseca, Luis L.
Joyner, Chester J.
Galinski, Mary R.
Voit, Eberhard O.
author_facet Fonseca, Luis L.
Joyner, Chester J.
Galinski, Mary R.
Voit, Eberhard O.
author_sort Fonseca, Luis L.
collection PubMed
description BACKGROUND: Plasmodium vivax can cause severe malaria. The total parasite biomass during infections is correlated with the severity of disease but not necessarily quantified accurately by microscopy. This finding has raised the question whether there could be sub-populations of parasites that are not observed in peripheral blood smears but continue to contribute to the increase in parasite numbers that drive pathogenesis. Non-human primate infection models utilizing the closely related simian malaria parasite Plasmodium cynomolgi hold the potential for quantifying the magnitude of possibly unobserved infected red blood cell (iRBC) populations and determining how the presence of this hidden reservoir correlates with disease severity. METHODS: Time series data tracking the longitudinal development of parasitaemia in five Macaca mulatta infected with P. cynomolgi were used to design a computational model quantifying iRBCs that circulate in the blood versus those that are not detectable and are termed here as ‘concealed’. This terminology is proposed to distinguish such observations from the deep vascular and widespread ‘sequestration’ of Plasmodium falciparum iRBCs, which is governed by distinctly different molecular mechanisms. RESULTS: The computational model presented here clearly demonstrates that the observed growth data of iRBC populations are not consistent with the known biology and blood-stage cycle of P. cynomolgi. However, the discrepancies can be resolved when a sub-population of concealed iRBCs is taken into account. The model suggests that the early growth of a hidden parasite sub-population has the potential to drive disease. As an alternative, the data could be explained by the sequential release of merozoites from the liver over a number of days, but this scenario seems less likely. CONCLUSIONS: Concealment of a non-circulating iRBC sub-population during P. cynomolgi infection of M. mulatta is an important aspect of this successful host–pathogen relationship. The data also support the likelihood that a sub-population of iRBCs of P. vivax has a comparable means to become withdrawn from the peripheral circulation. This inference has implications for understanding vivax biology and pathogenesis and stresses the importance of considering a concealed parasite reservoir with regard to vivax epidemiology and the quantification and treatment of P. vivax infections. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-2008-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-56081622017-09-25 A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta Fonseca, Luis L. Joyner, Chester J. Galinski, Mary R. Voit, Eberhard O. Malar J Research BACKGROUND: Plasmodium vivax can cause severe malaria. The total parasite biomass during infections is correlated with the severity of disease but not necessarily quantified accurately by microscopy. This finding has raised the question whether there could be sub-populations of parasites that are not observed in peripheral blood smears but continue to contribute to the increase in parasite numbers that drive pathogenesis. Non-human primate infection models utilizing the closely related simian malaria parasite Plasmodium cynomolgi hold the potential for quantifying the magnitude of possibly unobserved infected red blood cell (iRBC) populations and determining how the presence of this hidden reservoir correlates with disease severity. METHODS: Time series data tracking the longitudinal development of parasitaemia in five Macaca mulatta infected with P. cynomolgi were used to design a computational model quantifying iRBCs that circulate in the blood versus those that are not detectable and are termed here as ‘concealed’. This terminology is proposed to distinguish such observations from the deep vascular and widespread ‘sequestration’ of Plasmodium falciparum iRBCs, which is governed by distinctly different molecular mechanisms. RESULTS: The computational model presented here clearly demonstrates that the observed growth data of iRBC populations are not consistent with the known biology and blood-stage cycle of P. cynomolgi. However, the discrepancies can be resolved when a sub-population of concealed iRBCs is taken into account. The model suggests that the early growth of a hidden parasite sub-population has the potential to drive disease. As an alternative, the data could be explained by the sequential release of merozoites from the liver over a number of days, but this scenario seems less likely. CONCLUSIONS: Concealment of a non-circulating iRBC sub-population during P. cynomolgi infection of M. mulatta is an important aspect of this successful host–pathogen relationship. The data also support the likelihood that a sub-population of iRBCs of P. vivax has a comparable means to become withdrawn from the peripheral circulation. This inference has implications for understanding vivax biology and pathogenesis and stresses the importance of considering a concealed parasite reservoir with regard to vivax epidemiology and the quantification and treatment of P. vivax infections. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-2008-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-09-18 /pmc/articles/PMC5608162/ /pubmed/28923058 http://dx.doi.org/10.1186/s12936-017-2008-4 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Fonseca, Luis L.
Joyner, Chester J.
Galinski, Mary R.
Voit, Eberhard O.
A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta
title A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta
title_full A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta
title_fullStr A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta
title_full_unstemmed A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta
title_short A model of Plasmodium vivax concealment based on Plasmodium cynomolgi infections in Macaca mulatta
title_sort model of plasmodium vivax concealment based on plasmodium cynomolgi infections in macaca mulatta
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608162/
https://www.ncbi.nlm.nih.gov/pubmed/28923058
http://dx.doi.org/10.1186/s12936-017-2008-4
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