Research

Integrative analysis of intraerythrocytic differentially expressed transcripts yields novel insights into the biology of Plasmodium falciparum

Raphael D Isokpehi and Winston A Hide

South African National Bioinformatics Institute, University of the Western Cape, Bellville 7535, South Africa

author email corresponding author email

Malaria Journal 2003, 2:38doi:10.1186/1475-2875-2-38

Published:	14 November 2003

Abstract

Background

The intraerythrocytic development of Plasmodium falciparum, the most virulent human malaria parasite involves asexual and gametocyte stages. There has been a significant increase in disparate datasets derived from genomic and post-genomic analysis of the parasite that necessitates delivery of integrated analysis from which biological processes important to the survival of the parasite can be determined.

Methods

In order to resolve genes associated with stage differentially expressed transcripts, we have developed and implemented an integrative approach that combines evidence from P. falciparum expressed sequence tags (ESTs), genomic, microarray, proteomic and gene ontology data.

Results

A total of 143 gametocyte-overexpressed and 51 asexual-overexpressed transcripts were identified. A subset of 74 genes associated with these transcripts showed evidence of stage-correlated protein expression, of which 53 have not been experimentally characterised. Our study has revealed (1) possible regulatory mechanisms in malaria parasites' gametocyte maturation, (2) correlation between EST and microarray data for a P. falciparum gene family to present unique EST-derived information, (3) candidate drug and antigenic targets on which computational and experimental studies can be performed, and (4) the need for more empirical studies on gene and protein expression in malaria parasites.

Conclusion

Applying different domains of data to the same underlying gene set has yielded novel insights into the biology of the parasite and presents an approach to appraise critically the data quality of post-genomic datasets from malaria parasites.