A SYSTEMS BIOLOGY APPROACH TO STUDY THE DYNAMICS OF MEMBRANE MICRODOMAINS IN MALARIA PARASITES.

In recent years, several computational methods have been developed to predict protein-protein interactions at a genome-wide level. Among them, a Bayesian approach has been proposed to integrate “-omics” data from diverse sources, and reconstruct probabilistic global interactomes. In order to apply this method to Plasmodium falciparum, the most virulent agent of the human malaria, we generated novel genomic data sets and gene expression profiles. In particular, we performed a re-assessment of the phylogenetic profile method proposing a new strategy to select reference genomes and adopting a novel measure of similarity. We also produced a new set of rosetta stone data on the basis of a large number of non-redundant genomes used as a reference set. Furthermore, diverse transcriptomic data have been organized to obtain gene expression profiles covering the entire intra-erythrocytic Plasmodium life-cycle. All data were then integrated to predict a global P. falciparum protein-protein interaction network. To gain insights on function and dynamics of specialized membrane compartments (lipid rafts), during P. falciparum development, we filtered our global interactome with stage-specific lipid raft proteomic data. Functional and topological studies of the obtained stage-specific interactomes were undertaken. Our results revealed a conserved subnetwork, the lipid raft “functional core”, involved in fundamental parasite processes and dynamic clusters populated of stage-specific proteins, responsible for remodeling of lipid raft organization.