The Journal of Infectious DiseasesGenomicsPeer-reviewed journal article
Transcriptome analysis of Plasmodium falciparum isolates from Benin reveals specific gene expression associated with cerebral malaria
Émilie Guillochon, Jérémy FraeringiD, Valentin JosteiD, Claire KamaliddiniD, Bertin VianouiD, Ludivine Houzé, Laura G. BaudriniD, Jean‐François FaucheriD, Agnès AubouyiD, Sandrine HouzéiD, Michel CotiD, Nicolas ArgyiD, Olivier TaboureauiD, Gwladys I BertiniD, NeuroCM group, Jules Maroufou Alao, Dissou AffolabiiD, Bibiane Biokou, Jean-Eudes Degbelo, Philippe DeloroniD, Latifou Dramane, Sayeh Jafari‐GuemouriiD, Anaïs LabrunieiD, Yélé Ladipo, Thomas Lathiere, , Brigitte Techer
Abstract
The host and parasitic factors leading to cerebral malaria (CM) are not yet fully elucidated and CM Plasmodium falciparum isolates transcriptome profile remains largely unknown. Based on RNA-seq data from 15 CM and 15 uncomplicated malaria (UM) children from Benin, we identified an increased ring stage signature in CM parasites. Reduced circulating time may result from a higher adherence ability of CM isolates and consistent with this hypothesis, we measured an overexpression of var genes in CM. var genes domains expression was more restricted in CM isolates compared to UM, reflecting the specific binding to receptors in host brain endothelium capillaries. However, ICAM-1 binding motif was found expressed in both CM and UM, questioning its role in PfEMP1 adhesion to ICAM-1 receptor. UM isolates increased circulation time may also be modulated by a more efficient immune response against infected erythrocytes surface proteins, which we could not demonstrate on our cohort. Identification of deregulated genes involved in adhesion, excluding variant surface antigens, also supports the hypothesis of an increased CM adhesion capacity. Finally, numerous upregulated genes involved in entry into host pathway were found, reflecting a greater erythrocytes invasion capacity of CM parasites.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 22
- FWCI
- 3.97
- Field percentile
- top 6%
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