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疟原虫恶性疟原虫中蛋白质-蛋白质相互作用和转录调控的共表达网络。

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

机构信息

School of Life Sciences, Fudan University, 220 Handan Road, Shanghai 200433, PR China.

出版信息

Gene. 2013 Apr 10;518(1):7-16. doi: 10.1016/j.gene.2012.11.092. Epub 2012 Dec 26.

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.

摘要

背景

疟疾仍然是最严重的全球传染病之一,对人类健康和经济发展构成重大威胁。基于网络的生物分析是一种从网络角度揭示关键基因和生物过程的有前途的方法,从单个基因特征无法识别。

结果

我们整合基因共表达谱与蛋白质-蛋白质相互作用和转录调控信息,构建了恶性疟原虫的综合基因共表达网络。基于该网络,我们使用 ICE(迭代聚类枚举)算法识别了 10 个核心模块,这些模块对于红细胞内发育周期(IDC)阶段的疟原虫发育至关重要。在每个模块中,所有基因由于共同调节或形成蛋白质复合物而高度相关。其中一些基因在三个接近的 IDC 阶段之间被识别为差异共表达。编码前体 mRNA 加工剪接因子 8 产物的 prpf8(PFD0265w)基因被鉴定为 IDC 阶段的 DCGs(差异共表达基因),尽管该基因功能在以前的研究中很少报道。通过整合物种特异性基因预测和差异共表达基因检测,我们发现一些模块可以根据这些模块中的一些基因执行物种特异性功能,例如模块 10。此外,为了揭示恶性疟原虫入侵红细胞的潜在机制,我们从基因共表达网络中使用 Steiner 树算法识别入侵子网络。基于子网的分析表明,一些重要的疟原虫特异性基因可以在寄生虫入侵过程中相互协作并共同调节,包括 PfRH2a(PF13_0198)和 PfRH2b(MAL13P1.176)的对头基因对。

结论

本研究基于基因共表达网络,可以深入了解发病机制,甚至毒力和恶性疟原虫发育的机制。

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