Newaz Khalique, Sriram K, Bera Debajyoti
Department of Computer Science, IIIT Delhi, New Delhi, India.
Center for Computational Biology, IIIT Delhi, New Delhi, India.
PLoS One. 2015 Dec 8;10(12):e0144389. doi: 10.1371/journal.pone.0144389. eCollection 2015.
Prion diseases are transmissible neurodegenerative diseases that arise due to conformational change of normal, cellular prion protein (PrPC) to protease-resistant isofrom (rPrPSc). Deposition of misfolded PrpSc proteins leads to an alteration of many signaling pathways that includes immunological and apoptotic pathways. As a result, this culminates in the dysfunction and death of neuronal cells. Earlier works on transcriptomic studies have revealed some affected pathways, but it is not clear which is (are) the prime network pathway(s) that change during the disease progression and how these pathways are involved in crosstalks with each other from the time of incubation to clinical death. We perform network analysis on large-scale transcriptomic data of differentially expressed genes obtained from whole brain in six different mouse strain-prion strain combination models to determine the pathways involved in prion diseases, and to understand the role of crosstalks in disease propagation. We employ a notion of differential network centrality measures on protein interaction networks to identify the potential biological pathways involved. We also propose a crosstalk ranking method based on dynamic protein interaction networks to identify the core network elements involved in crosstalk with different pathways. We identify 148 DEGs (differentially expressed genes) potentially related to the prion disease progression. Functional association of the identified genes implicates a strong involvement of immunological pathways. We extract a bow-tie structure that is potentially dysregulated in prion disease. We also propose an ODE model for the bow-tie network. Predictions related to diseased condition suggests the downregulation of the core signaling elements (PI3Ks and AKTs) of the bow-tie network. In this work, we show using transcriptomic data that the neuronal dysfunction in prion disease is strongly related to the immunological pathways. We conclude that these immunological pathways occupy influential positions in the PFNs (protein functional networks) that are related to prion disease. Importantly, this functional network involvement is prevalent in all the five different mouse strain-prion strain combinations that we studied. We also conclude that the dysregulation of the core elements of the bow-tie structure, which belongs to PI3K-Akt signaling pathway, leads to dysregulation of the downstream components corresponding to other biological pathways.
朊病毒疾病是一种可传播的神经退行性疾病,它是由于正常的细胞朊病毒蛋白(PrPC)构象转变为蛋白酶抗性异构体(rPrPSc)而引发的。错误折叠的PrpSc蛋白沉积会导致包括免疫和凋亡途径在内的许多信号通路发生改变。结果,这最终导致神经元细胞功能障碍和死亡。早期的转录组学研究工作已经揭示了一些受影响的途径,但尚不清楚在疾病进展过程中哪个(些)是主要的网络途径发生了变化,以及从潜伏期到临床死亡期间这些途径是如何相互串扰的。我们对从六种不同小鼠品系 - 朊病毒株组合模型的全脑中获得的差异表达基因的大规模转录组数据进行网络分析,以确定参与朊病毒疾病的途径,并了解串扰在疾病传播中的作用。我们在蛋白质相互作用网络上采用差异网络中心性度量的概念来识别潜在的生物途径。我们还基于动态蛋白质相互作用网络提出了一种串扰排名方法,以识别与不同途径发生串扰的核心网络元件。我们确定了148个与朊病毒疾病进展潜在相关的差异表达基因(DEG)。所鉴定基因的功能关联表明免疫途径密切参与其中。我们提取了一种在朊病毒疾病中可能失调的领结结构。我们还为领结网络提出了一个常微分方程模型。与疾病状况相关的预测表明领结网络的核心信号元件(PI3K和AKT)下调。在这项工作中,我们利用转录组数据表明,朊病毒疾病中的神经元功能障碍与免疫途径密切相关。我们得出结论,这些免疫途径在与朊病毒疾病相关的蛋白质功能网络(PFN)中占据有影响力的位置。重要的是,这种功能网络参与在我们研究的所有五种不同小鼠品系 - 朊病毒株组合中都很普遍。我们还得出结论,属于PI3K - Akt信号通路的领结结构核心元件的失调会导致对应于其他生物途径的下游成分失调。