A systems-level gene regulatory network model for Plasmodium falciparum.
A systems-level gene regulatory network model for Plasmodium falciparum.
复制标题
恶性疟原虫系统水平的基因调控网络模型。
DOI：
10.1093/nar/gkaa1245
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发表时间：
2021-05-21
影响因子：
14.9
通讯作者：
Aitchison JD
中科院分区：
文献类型：
--
作者：
Neal ML;Wei L;Peterson E;Arrieta-Ortiz ML;Danziger SA;Baliga NS;Kaushansky A;Aitchison JD
恶性疟原虫（最致命的疟疾寄生虫）的许多基因调控过程仍然知之甚少。为了开发一个全面的指南来探索这种生物的基因调控网络，我们使用一种经过验证的机器学习方法来预测转录调控因子与其靶标之间的相互作用，建立了恶性疟原虫基因调控的系统级模型。由此产生的网络准确地预测了不同研究小组在不同实验室和现场环境中收集的寄生虫独立转录组数据集中转录连贯基因调控程序的表达水平。因此，我们的研究结果表明，我们的基因调控模型具有预测能力和实用性，可以作为一种假设生成工具，用于阐明恶性疟原虫临床相关的基因调控机制。利用我们确定的一组调控程序，我们还基于基因表达一致性研究了青蒿素耐药性的相关因素。我们报道耐药性与许多调控程序的不连贯表达有关，包括那些与红细胞-宿主接合相关的控制基因。这些结果表明，青蒿素敏感性降低的寄生虫种群在转录上更具异质性。这种模式与寄生虫利用下注对冲策略使种群多样化的模型一致，使一个亚种群更能驾驭药物治疗。
Many of the gene regulatory processes of Plasmodium falciparum, the deadliest malaria parasite, remain poorly understood. To develop a comprehensive guide for exploring this organism's gene regulatory network, we generated a systems-level model of P. falciparum gene regulation using a well-validated, machine-learning approach for predicting interactions between transcription regulators and their targets. The resulting network accurately predicts expression levels of transcriptionally coherent gene regulatory programs in independent transcriptomic data sets from parasites collected by different research groups in diverse laboratory and field settings. Thus, our results indicate that our gene regulatory model has predictive power and utility as a hypothesis-generating tool for illuminating clinically relevant gene regulatory mechanisms within P. falciparum. Using the set of regulatory programs we identified, we also investigated correlates of artemisinin resistance based on gene expression coherence. We report that resistance is associated with incoherent expression across many regulatory programs, including those controlling genes associated with erythrocyte-host engagement. These results suggest that parasite populations with reduced artemisinin sensitivity are more transcriptionally heterogenous. This pattern is consistent with a model where the parasite utilizes bet-hedging strategies to diversify the population, rendering a subpopulation more able to navigate drug treatment.
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影响因子：
7.7
作者：
Caro F;Ahyong V;Betegon M;DeRisi JL
通讯作者：
DeRisi JL
影响因子：
9.8
作者：
Bozdech, Zbynek;Llinas, Manuel;Pulliam, Brian Lee;Wong, Edith D;Zhu, Jingchun;DeRisi, Joseph L
通讯作者：
DeRisi, Joseph L
影响因子：
14.9
作者：
The Gene Ontology Consortium
通讯作者：
The Gene Ontology Consortium
影响因子：
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作者：
Campbell TL;De Silva EK;Olszewski KL;Elemento O;Llinás M
通讯作者：
Llinás M
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3.7
作者：
Iwanaga S;Kaneko I;Kato T;Yuda M
通讯作者：
Yuda M