Malaria is one of the deadliest infectious diseases, threatening half a billion humans worldwide with a yearly death toll of 1 to 2 million people, mainly in developing countries. Malaria is due to infections by protozoan parasites of the Plasmodium genus, transmitted by bites of female Anopheles mosquitoes. Of the four species that infect humans, P.falciparum causes the greatest incidence of illness and death.

The genome of P.falciparum has been published in 2002. It is an atypical genome with a large proportion of A/T (80%) and the presence of long low-complexity insertions of unknown function. Around 60% of the ~5500 predicted genes do not have sufficient similarity to characterized genes in other species to justify provision of functional assignments and have no annotation in the Gene Ontology. Although this situation may be explained by the existence of genes that are unique to the Plasmodium genus, it is further exacerbated by the high evolutionary distance between P.falciparum and other sequenced organisms, which makes homology detection particularly difficult.

Despite sustained efforts to combat the disease, safe and affordable new drugs, and new drug targets, are still required to circumvent drug resistance outbreaks. To this end, a fundamental understanding of how parasite genes are regulated is critical to developing novel therapeutic strategies against this organism. New insights into the complex processes that regulate genes involved in key functions such as transmission success, immune evasion, and drug resistance are expected to provide promising new drug targets. In addition, this can also shed light on the mode of action of known drugs, and help understanding the P.falciparum resistance mechanisms.

Numerous high-throughput studies have screened P.falciparum gene expression under various conditions, showing a tightly controlled and intricate gene expression program. However, apart from a few specific genes, we remain largely ignorant of the mechanisms underlying gene control, and, more specifically, on the relative role of transcriptional and post-transcriptional regulation in the parasite.

This project aims at developing new computational methods to decipher the mechanisms of gene expression regulation in P.falciparum. The objectives are to identify both new drug targets and targets of already known drugs. Three tasks compose the core of the project: 1) Searching for new transcription factors into the P.falciparum proteome; 2) Investigating to what extent chromatin modification and post-transcriptional processes control steady-state mRNA; 3) Characterizing the transcriptomic response of P.falciparum to known drugs. From a computational perspective, this involves the development of new approaches for homology detection, high-throughput data modeling, and feature selection. We will use machine learning approaches involving HMMs, mixture models, time series analysis, clustering, and various learning algorithms able to cope with the inherent nature of most post-genomic data.

PlasmoExpress is a collaboration between the bioinformatic team of the LIRMM (Montpellier) and three biology laboratories involved in the study of P.falciparum: the Eric Maréchal's team (Grenoble), the Henri Vial's team (Montpellier), and the Karine Le Roch's laboratory in the University of California (Riverside).