Analysis of the Plasmodium falciparum proteome by high-accuracy mass spectrometry

Edwin Lasonder, Yasushi Ishihama, Jens S. Andersen, Adriaan M. W. Vermunt, Arnab Pain, Robert W. Sauerwein, Wijnand M. C. Eling, Neil Hall, Andrew P. Waters, Hendrik G. Stunnenberg () and Matthias Mann ()
Additional contact information
Edwin Lasonder: University of Southern Denmark
Yasushi Ishihama: University of Southern Denmark
Jens S. Andersen: University of Southern Denmark
Adriaan M. W. Vermunt: University of Nijmegen
Arnab Pain: The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus
Robert W. Sauerwein: University Medical Centre
Wijnand M. C. Eling: University Medical Centre
Neil Hall: The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus
Andrew P. Waters: Leiden University Medical Center
Hendrik G. Stunnenberg: University of Nijmegen
Matthias Mann: University of Southern Denmark

Nature, 2002, vol. 419, issue 6906, 537-542

Abstract: Abstract The annotated genomes of organisms define a ‘blueprint’ of their possible gene products. Post-genome analyses attempt to confirm and modify the annotation and impose a sense of the spatial, temporal and developmental usage of genetic information by the organism. Here we describe a large-scale, high-accuracy (average deviation less than 0.02 Da at 1,000 Da) mass spectrometric proteome analysis1,2,3 of selected stages of the human malaria parasite Plasmodium falciparum. The analysis revealed 1,289 proteins of which 714 proteins were identified in asexual blood stages, 931 in gametocytes and 645 in gametes. The last two groups provide insights into the biology of the sexual stages of the parasite, and include conserved, stage-specific, secreted and membrane-associated proteins. A subset of these proteins contain domains that indicate a role in cell–cell interactions, and therefore can be evaluated as potential components of a malaria vaccine formulation. We also report a set of peptides with significant matches in the parasite genome but not in the protein set predicted by computational methods.

Date: 2002
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DOI: 10.1038/nature01111

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