Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, United States.
Department of Mathematics, North Carolina State University, Raleigh, NC, United States.
Front Immunol. 2019 Jul 24;10:1736. doi: 10.3389/fimmu.2019.01736. eCollection 2019.
The human innate immune response, particularly the type-I interferon (IFN) response, is highly robust and effective first line of defense against virus invasion. IFN molecules are produced and secreted from infected cells upon virus infection and recognition. They then act as signaling/communication molecules to activate an antiviral response in neighboring cells so that those cells become refractory to infection. Previous experimental studies have identified the detailed molecular mechanisms for the IFN signaling and response. However, the principles underlying how host cells use IFN to communicate with each other to collectively and robustly halt an infection is not understood. Here we take a multiplex network modeling approach to provide a theoretical framework to identify key factors that determine the effectiveness of the IFN response against virus infection of a host. In this approach, we consider the virus spread among host cells and the interferon signaling to protect host cells as a competition process on a two-layer multiplex network. We focused on two types of network topology, i.e., the Erdős-Rényi (ER) network and the Geometric Random (GR) network, which represent the scenarios when infection of cells is mostly well mixed (e.g., in the blood) and when infection is spatially segregated (e.g., in tissues), respectively. We show that in general, the IFN response works effectively to stop viral infection when virus infection spreads spatially (a most likely scenario for initial virus infection of a host at the peripheral tissue). Importantly, we show that the effectiveness of the IFN response is robust against large variations in the distance of IFN diffusion as long as IFNs diffuse faster than viruses and they can effectively induce antiviral responses in susceptible host cells. This suggests that the effectiveness of the IFN response is insensitive to the specific arrangement of host cells in peripheral tissues. Thus, our work provides a quantitative explanation of why the IFN response can serve an effective and robust response in different tissue types to a wide range of viral infections of a host.
人类先天免疫反应,特别是 I 型干扰素(IFN)反应,是抵御病毒入侵的高度强大和有效的第一道防线。IFN 分子在病毒感染和识别后由感染细胞产生和分泌。然后,它们作为信号/通信分子,激活邻近细胞中的抗病毒反应,使这些细胞对感染产生抗性。先前的实验研究已经确定了 IFN 信号转导和反应的详细分子机制。然而,宿主细胞如何利用 IFN 相互通信以集体和强大地阻止感染的原理尚不清楚。在这里,我们采用多重网络建模方法,为识别决定 IFN 反应对宿主病毒感染有效性的关键因素提供了一个理论框架。在这种方法中,我们将病毒在宿主细胞中的传播和干扰素信号保护宿主细胞视为双层多重网络上的竞争过程。我们专注于两种类型的网络拓扑结构,即 Erdős-Rényi(ER)网络和几何随机(GR)网络,它们分别代表细胞感染高度混合(例如,在血液中)和感染空间隔离(例如,在组织中)的情况。我们表明,一般来说,当病毒感染在空间上传播时(宿主外周组织初始病毒感染最有可能的情况),IFN 反应有效地阻止病毒感染。重要的是,我们表明,只要 IFN 扩散速度快于病毒,并且能够有效地诱导易感宿主细胞中的抗病毒反应,IFN 反应的有效性就对 IFN 扩散距离的大变化具有鲁棒性。这表明 IFN 反应的有效性对周围组织中宿主细胞的特定排列不敏感。因此,我们的工作提供了一个定量解释,说明为什么 IFN 反应可以在不同的组织类型中对宿主的广泛病毒感染产生有效和强大的反应。