Disease-specific modules and potential hub genes for intervention strategies: A co-expression network-based approach for Plasmodium falciparum clinical isolates

Systems biology approaches that are based on gene expression and bioinformatics analysis have been successful in predicting the functions of many genes in Plasmodium falciparum, a protozoan parasite responsible for most of the deaths due to malaria. However, methods that can provide information about the biological processes that are active in this parasite during complicated malaria conditions have not been employed yet. Here, we report the use of a weighted gene co-expression-based network analysis approach to construct a P. falciparum in vivo systems network. Gene expression profiles of 21 P. falciparum clinical isolates were utilized to construct the same. A total of 20 highly interacting modules were identified post network creation, of which at least 10% members of 12 modules were found to be differentially regulated in complicated isolates compared to uncomplicated isolates. Enrichment analysis identified biological processes like oxidation-reduction, electron transport chain, protein synthesis, ubiquitin-dependent catabolic processes, RNA binding and purine nucleotide metabolic processes to be associated with these modules. Additionally, for each module, highly connected hub genes were identified. Detailed functional analysis of many hub genes with known annotated function underline their importance in parasite development and survival, suggesting that other hub genes with unknown function might be playing crucial roles in parasite biology and are potential candidate for intervention strategies. Plasmodium falciparum isolates were collected from patients (n=21) with differing clinical conditions. The patients exhibited symptoms categorized as uncomplicated (n=5) or complicated malaria (n=16). Criteria for determination of complicated disease were based on World Health Organization year 2000 guidelines. Microarray-based transcriptional profiling was carried out to evaluate the performance of the array.measure expression of genes in each sample.