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Co-expression network with protein-protein interaction and transcription regulation in malaria parasite Plasmodium falciparum. | LitMetric

AI Article Synopsis

  • - Malaria remains a critical global health issue, and network-based biological analysis can reveal important genes and processes that individual gene studies might miss, aiding in the fight against this disease.
  • - Researchers created a comprehensive gene co-expression network for the malaria parasite Plasmodium falciparum, identifying 10 essential modules linked to its development during specific life cycle stages.
  • - The study discovered key genes, including prpf8, that are differentially co-expressed during the parasite's life cycle, and identified potential cooperation among crucial invasion genes, enhancing the understanding of how the parasite invades red blood cells.

Article Abstract

Background: Malaria continues to be one of the most severe global infectious diseases, as a major threat to human health and economic development. Network-based biological analysis is a promising approach to uncover key genes and biological processes from a network viewpoint, which could not be recognized from individual gene-based signatures.

Results: We integrated gene co-expression profile with protein-protein interaction and transcriptional regulation information to construct a comprehensive gene co-expression network of Plasmodium falciparum. Based on this network, we identified 10 core modules by using ICE (Iterative Clique Enumeration) algorithm, which were essential for malaria parasite development in intraerythrocytic developmental cycle (IDC) stages. In each module, all genes were highly correlated probably due to co-regulation or formation of a protein complex. Some of these genes were recognized to be differentially coexpressed among three close-by IDC stages. The gene of prpf8 (PFD0265w) encoding pre-mRNA processing splicing factor 8 product was identified as DCGs (differentially co-expressed genes) among IDC stages, although this gene function was seldom reported in previous researches. Integrating the species-specific gene prediction and differential co-expression gene detection, we found some modules could perform species-specific functions according to some of genes in these modules were species-specific genes, like the module 10. Furthermore, in order to reveal the underlying mechanisms of the erythrocyte invasion by P. falciparum, Steiner Tree algorithm was employed to identify the invasion subnetwork from our gene co-expression network. The subnetwork-based analysis indicated that some important Plasmodium parasite specific genes could corporate with each other and be co-regulated during the parasite invasion process, which including a head-to-head gene pair of PfRH2a (PF13_0198) and PfRH2b (MAL13P1.176).

Conclusions: This study based on gene co-expression network could shed new insights on the mechanisms of pathogenesis, even virulence and P. falciparum development.

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Source
http://dx.doi.org/10.1016/j.gene.2012.11.092DOI Listing

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