Das A, Sahu W, Ojha DK, Reddy KS, Suar M. Comparative Analysis of Host Metabolic Alterations in Murine Malaria Models with Uncomplicated or Severe Malaria.
J Proteome Res 2022;
21:2261-2276. [PMID:
36169658 DOI:
10.1021/acs.jproteome.2c00123]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Malaria varies in severity, with complications ranging from uncomplicated to severe malaria. Severe malaria could be attributed to peripheral hyperparasitemia or cerebral malaria. The metabolic interactions between the host and Plasmodium species are yet to be understood during these infections of varied pathology and severity. An untargeted metabolomics approach utilizing the liquid chromatography-mass spectrometry platform has been used to identify the affected host metabolic pathways and associated metabolites in the serum of murine malaria models with uncomplicated malaria, hyperparasitemia, and experimental cerebral malaria. We report that mice with malaria share similar metabolic attributes like higher levels of bile acids, bile pigments, and steroid hormones that have been reported for human malaria infections. Moreover, in severe malaria, upregulated levels of metabolites like phenylalanine, histidine, valine, pipecolate, ornithine, and pantothenate, with decreased levels of arginine and hippurate, were observed. Metabolites of sphingolipid metabolism were upregulated in experimental cerebral malaria. Higher levels of 20-hydroxy-leukotriene B4 and epoxyoctadecamonoenoic acids were found in uncomplicated malaria, with lower levels observed for experimental cerebral malaria. Our study provides insights into host biology during different pathological stages of malaria disease and would be useful for the selection of animal models for evaluating diagnostic and therapeutic interventions against malaria. The raw data files are available via MetaboLights with the identifier MTBLS4387.
Collapse