Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting
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AuthorsAbdel-Haleem, Alyaa M.
Palsson, Bernhard O.
Lewis, Nathan E.
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Computational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
KAUST Grant NumberURF/1/1976-03
MetadataShow full item record
AbstractSeveral antimalarial drugs exist, but differences between life cycle stages among malaria species pose challenges for developing more effective therapies. To understand the diversity among stages and species, we reconstructed genome-scale models (GEMs) of metabolism for five life cycle stages and five species of Plasmodium spanning the blood, transmission, and mosquito stages. The stage-specific models of Plasmodium falciparum uncovered stage-dependent changes in central carbon metabolism and predicted potential targets that could affect several life cycle stages. The species-specific models further highlight differences between experimental animal models and the human-infecting species. Comparisons between human- and rodent-infecting species revealed differences in thiamine (vitamin B1), choline, and pantothenate (vitamin B5) metabolism. Thus, we show that genome-scale analysis of multiple stages and species of Plasmodium can prioritize potential drug targets that could be both anti-malarials and transmission blocking agents, in addition to guiding translation from non-human experimental disease models.
CitationAbdel-Haleem AM, Hefzi H, Mineta K, Gao X, Gojobori T, et al. (2018) Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting. PLOS Computational Biology 14: e1005895. Available: http://dx.doi.org/10.1371/journal.pcbi.1005895.
SponsorsAMAH, XG, KM, and TG acknowledge funding from King Abdullah University of Science and Technology (KAUST) and the Office of Sponsored Research (OSR) under Award No. URF/1/1976-03. NEL acknowledges generous support from the Novo Nordisk Foundation provided to the Center for Biosustainability at the Technical University of Denmark and funding from NIH (R35 GM119850-01 and R01 AI090141-05). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
PublisherPublic Library of Science (PLoS)
JournalPLOS Computational Biology
Except where otherwise noted, this item's license is described as 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.
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