A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum

Plasmodium falciparum DDX17 is an RNA helicase crucial for parasite development

Malaria is one of the major global health concerns still prevailing in this 21st century. Even the effect of artemisinin combination therapies (ACT) have declined and causing more mortality across the globe. Therefore, it is important to understand the basic biology of malaria parasite in order to find novel drug targets. Helicases play important role in nucleic acid metabolism and are components of cellular machinery in various organisms. In this manuscript we have performed the biochemical characterization of homologue of DDX17 from Plasmodium falciparum (PfDDX17). Our results show that PfDDX17 is an active RNA helicase and uses mostly ATP for its function. The qRT-PCR experiment results suggest that PfDDX17 is highly expressed in the trophozoite stage and it is localised mainly in the cytoplasm and in infected RBC (iRBC) membrane mostly in the trophozoite stage. The dsRNA knockdown study suggests that PfDDX17 is important for cell cycle progression. These studies report the biochemical functions of PfDDX17 helicase and further augment the fundamental knowledge about helicase families of P. falciparum.

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Biochemical characterization of homologue of DDX17 from Plasmodium falciparum (PfDDX17) is presented.

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Results show that PfDDX17 is an active RNA helicase and uses mostly ATP for its function.

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Results also suggest that PfDDX17 is highly expressed in the trophozoite stage.

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dsRNA knockdown study revealed that PfDDX17 is important for cell cycle progression.

Genome-Wide Analysis of Genetic Diversity in Plasmodium falciparum Isolates From China-Myanmar Border

Plasmodium falciparum isolates from China-Myanmar border (CMB) have experienced regional special selective pressures and adaptive evolution. However, the genomes of P. falciparum isolates from this region to date are poorly characterized. Herein, we performed whole-genome sequencing of 34 P. falciparum isolates from CMB and a series of genome-wide sequence analyses to reveal their genetic diversity, population structures, and comparisons with the isolates from other epidemic regions (Thai-Cambodia border, Thai-Myanmar border, and West Africa). Totally 59,720 high-quality single-nucleotide polymorphisms (SNPs) were identified in the P. falciparum isolates from CMB, with average nucleotide diversity (π = 4.59 × 10^-4) and LD decay (132 bp). The Tajima's D and Fu and Li's D values of the CMB isolates were -0.8 (p < 0.05) and -0.84 (p < 0.05), respectively, suggesting a demographic history of recent population expansion or purifying selection. Moreover, 78 genes of the parasite were identified that could be under positive selection, including those genes conferring drug resistance such as pfubp1. In addition, 33 SNPs were identified for tracing the source of the parasites with a high accuracy by analysis of the most differential SNPs among the four epidemic regions. Collectively, our data demonstrated high diversity of the CMB isolates' genomes forming a distinct population, and the identification of 33-SNP barcode provides a valuable surveillance of parasite migration among the regions.

Predicting and exploring network components involved in pathogenesis in the malaria parasite via novel subnetwork alignments

BACKGROUND

Malaria is a major health threat, affecting over 40% of the world's population. The latest report released by the World Health Organization estimated about 207 million cases of malaria infection, and about 627,000 deaths in 2012 alone. During the past decade, new therapeutic targets have been identified and are at various stages of characterization, thanks to the emerging omics-based technologies. However, the mechanism of malaria pathogenesis remains largely unknown. In this paper, we employ a novel neighborhood subnetwork alignment approach to identify network components that are potentially involved in pathogenesis.

RESULTS

Our module-based subnetwork alignment approach identified 24 functional homologs of pathogenesis-related proteins in the malaria parasite P. falciparum, using the protein-protein interaction networks in Escherichia coli as references. Eighteen out of these 24 proteins are associated with 418 other proteins that are related to DNA replication, transcriptional regulation, translation, signaling, metabolism, cell cycle regulation, as well as cytoadherence and entry to the host.

CONCLUSIONS

The subnetwork alignments and subsequent protein-protein association network mining predicted a group of malarial proteins that may be involved in parasite development and parasite-host interaction, opening a new systems-level view of parasite pathogenesis and virulence.

Heavy path mining of protein-protein associations in the malaria parasite

Annotating and understanding the function of proteins and other elements in a genome can be difficult in the absence of a well-studied and evolutionarily close relative. The causative agent of malaria, one of the oldest and most deadly global infectious diseases, is a good example of this problem. The burden of malaria is huge and there is a pressing need for new, more effective antimalarial strategies. However, techniques such as homology-dependent annotation transfer are severely impaired in this parasite because there are no well-understood close relatives. To circumvent this approach we developed a network-based method that uses a heavy path network-mining algorithm. We uncovered the protein-protein associations that are implicated in important cellular processes including genome integrity, DNA repair, transcriptional regulation, invasion, and pathogenesis, thus demonstrating the utility of this method. The URL of the source code for super-sequence mining method is http://www.cs.utsa.edu/~korkmaz/research/heavy-path-mining/.