• Medientyp: E-Artikel
  • Titel: MaHPIC malaria systems biology data from Plasmodium cynomolgi sporozoite longitudinal infections in macaques
  • Beteiligte: DeBarry, Jeremy D.; Nural, Mustafa V.; Pakala, Suman B.; Nayak, Vishal; Warrenfeltz, Susanne; Humphrey, Jay; Lapp, Stacey A.; Cabrera-Mora, Monica; Brito, Cristiana F. A.; Jiang, Jianlin; Saney, Celia L.; Hankus, Allison; Stealey, Hannah M.; DeBarry, Megan B.; Lackman, Nicolas; Legall, Noah; Lee, Kevin; Tang, Yan; Gupta, Anuj; Trippe, Elizabeth D.; Bridger, Robert R.; Weatherly, Daniel Brent; Peterson, Mariko S.; Jiang, Xuntian; [...]
  • Erschienen: Springer Science and Business Media LLC, 2022
  • Erschienen in: Scientific Data, 9 (2022) 1
  • Sprache: Englisch
  • DOI: 10.1038/s41597-022-01755-y
  • ISSN: 2052-4463
  • Schlagwörter: Library and Information Sciences ; Statistics, Probability and Uncertainty ; Computer Science Applications ; Education ; Information Systems ; Statistics and Probability
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  • Beschreibung: AbstractPlasmodium cynomolgi causes zoonotic malarial infections in Southeast Asia and this parasite species is important as a model for Plasmodium vivax and Plasmodium ovale. Each of these species produces hypnozoites in the liver, which can cause relapsing infections in the blood. Here we present methods and data generated from iterative longitudinal systems biology infection experiments designed and performed by the Malaria Host-Pathogen Interaction Center (MaHPIC) to delve deeper into the biology, pathogenesis, and immune responses of P. cynomolgi in the Macaca mulatta host. Infections were initiated by sporozoite inoculation. Blood and bone marrow samples were collected at defined timepoints for biological and computational experiments and integrative analyses revolving around primary illness, relapse illness, and subsequent disease and immune response patterns. Parasitological, clinical, haematological, immune response, and -omic datasets (transcriptomics, proteomics, metabolomics, and lipidomics) including metadata and computational results have been deposited in public repositories. The scope and depth of these datasets are unprecedented in studies of malaria, and they are projected to be a F.A.I.R., reliable data resource for decades.
  • Zugangsstatus: Freier Zugang