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Whole blood transcriptome changes following controlled human malaria infection in malaria pre-exposed volunteers correlate with parasite prepatent period.

Julian Rothen | Carl Murie | Jason Carnes | Atashi Anupama | Salim Abdulla | Mwajuma Chemba | Maxmillian Mpina | Marcel Tanner | B Kim Lee Sim | Stephen L Hoffman | Raphael Gottardo | Claudia Daubenberger | Ken Stuart
PloS one | 2018

Malaria continues to be one of mankind's most devastating diseases despite the many and varied efforts to combat it. Indispensable for malaria elimination and eventual eradication is the development of effective vaccines. Controlled human malaria infection (CHMI) is an invaluable tool for vaccine efficacy assessment and investigation of early immunological and molecular responses against Plasmodium falciparum infection. Here, we investigated gene expression changes following CHMI using RNA-Seq. Peripheral blood samples were collected in Bagamoyo, Tanzania, from ten adults who were injected intradermally (ID) with 2.5x104 aseptic, purified, cryopreserved P. falciparum sporozoites (Sanaria® PfSPZ Challenge). A total of 2,758 genes were identified as differentially expressed following CHMI. Transcriptional changes were most pronounced on day 5 after inoculation, during the clinically silent liver phase. A secondary analysis, grouping the volunteers according to their prepatent period duration, identified 265 genes whose expression levels were linked to time of blood stage parasitemia detection. Gene modules associated with these 265 genes were linked to regulation of transcription, cell cycle, phosphatidylinositol signaling and erythrocyte development. Our study showed that in malaria pre-exposed volunteers, parasite prepatent period in each individual is linked to magnitude and timing of early gene expression changes after ID CHMI.

Pubmed ID: 29920562

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NIAID NIH HHS, United States
    Id: U19 AI089986
  • Agency: NIAID NIH HHS, United States
    Id: U19 AI128914

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Ambion Inc. (tool)

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Software package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.

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edgeR (tool)

RRID:SCR_012802

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

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RSEM (tool)

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RRID:SCR_014583

Quality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.

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RRID:SCR_018419

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