Comparing Host Module Activation Patterns and Temporal Dynamics in Infection by Influenza H1N1 Viruses.

Irina Nudelman,Elena Zaslavsky,Stuart C Sealfon,Steven H Kleinstein,Raamesh Deshpande,German Nudelman,Daniil Kudrin,Chad L Myers,Boris M Hartmann

doi:10.3389/fimmu.2021.691758

Abstract

Influenza is a serious global health threat that shows varying pathogenicity among different virus strains. Understanding similarities and differences among activated functional pathways in the host responses can help elucidate therapeutic targets responsible for pathogenesis. To compare the types and timing of functional modules activated in host cells by four influenza viruses of varying pathogenicity, we developed a new DYNAmic MOdule (DYNAMO) method that addresses the need to compare functional module utilization over time. This integrative approach overlays whole genome time series expression data onto an immune-specific functional network, and extracts conserved modules exhibiting either different temporal patterns or overall transcriptional activity. We identified a common core response to influenza virus infection that is temporally shifted for different viruses. We also identified differentially regulated functional modules that reveal unique elements of responses to different virus strains. Our work highlights the usefulness of combining time series gene expression data with a functional interaction map to capture temporal dynamics of the same cellular pathways under different conditions. Our results help elucidate conservation of the immune response both globally and at a granular level, and provide mechanistic insight into the differences in the host response to infection by influenza strains of varying pathogenicity.

Highlights

IntroductionWhile most annual influenza strains are associated with a relatively low global infection rate and mortality, more widely infectious or lethal influenza virus strains arise periodically
The possibility of influenza virus pandemics remains a potent public health threat
As a motivation for our study was an observation made while investigating a time course microarray dataset of the responses to four strains of the influenza virus in human monocyte-derived dendritic cells (DCs) [27]

Summary

Introduction

While most annual influenza strains are associated with a relatively low global infection rate and mortality, more widely infectious or lethal influenza virus strains arise periodically. The swineorigin influenza pandemic in 2009 infected 20-50 percent of the population of some countries, it had a mortality rate comparable to that of seasonal influenza strains [2]. Individual seasonal and pandemic influenza strains vary in their infectivity and pathogenicity. The genetic mechanisms underlying the emergence of new viruses are relatively well understood, less is known about virus-host interaction effects that may influence influenza transmission or disease outcome. Implementing a computational approach to identify commonalities and differences in the host biological response to different influenza virus strains is important in providing insight into common and distinct components of the host response program that may contribute to pathogenicity

Methods

Results

Conclusion