Abstract

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.

Highlights

  • Virus infections and the resulting diseases are major challenges that our society faces today [1]

  • The multiplex network is modeled by a family of graphs Gm (Vm, Em) m=1 where all graphs share the same set of nodes i.e., V1 = V2 = ... = V = [n]

  • We first focused on multiplex networks where both layers are ER graphs as baseline models

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Summary

Introduction

Virus infections and the resulting diseases are major challenges that our society faces today [1]. One important determinant of the outcome of an infection is the innate immune response, the type-I interferon (IFN) response (“the IFN response” for short). It has been shown that the ability to evade host IFN response is an important determinant of viral replication [5,6,7], transmission [8], and host species range of viral infection [9]. Viruses that lack the ability to evade the innate immune response are not able to infect and replicate in a host [7, 8]. This demonstrates that the IFN response plays a crucial role in protecting hosts from virus invasion

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