Comprehensive Transcriptomic Analysis Identifies Novel Antiviral Factors Against Influenza A Virus Infection.

Ao Zhou,Xia Dong,Mengyun Liu,Bin Tang

doi:10.3389/fimmu.2021.632798

Abstract

Influenza A virus (IAV) has a higher genetic variation, leading to the poor efficiency of traditional vaccine and antiviral strategies targeting viral proteins. Therefore, developing broad-spectrum antiviral treatments is particularly important. Host responses to IAV infection provide a promising approach to identify antiviral factors involved in virus infection as potential molecular drug targets. In this study, in order to better illustrate the molecular mechanism of host responses to IAV and develop broad-spectrum antiviral drugs, we systematically analyzed mRNA expression profiles of host genes in a variety of human cells, including transformed and primary epithelial cells infected with different subtypes of IAV by mining 35 microarray datasets from the GEO database. The transcriptomic results showed that IAV infection resulted in the difference in expression of amounts of host genes in all cell types, especially those genes participating in immune defense and antiviral response. In addition, following the criteria of P<0.05 and |logFC|≥1.5, we found that some difference expression genes were overlapped in different cell types under IAV infection via integrative gene network analysis. IFI6, IFIT2, ISG15, HERC5, RSAD2, GBP1, IFIT3, IFITM1, LAMP3, USP18, and CXCL10 might act as key antiviral factors in alveolar basal epithelial cells against IAV infection, while BATF2, CXCL10, IFI44L, IL6, and OAS2 played important roles in airway epithelial cells in response to different subtypes of IAV infection. Additionally, we also revealed that some overlaps (BATF2, IFI44L, IFI44, HERC5, CXCL10, OAS2, IFIT3, USP18, OAS1, IFIT2) were commonly upregulated in human primary epithelial cells infected with high or low pathogenicity IAV. Moreover, there were similar defense responses activated by IAV infection, including the interferon-regulated signaling pathway in different phagocyte types, although the differentially expressed genes in different phagocyte types showed a great difference. Taken together, our findings will help better understand the fundamental patterns of molecular responses induced by highly or lowly pathogenic IAV, and the overlapped genes upregulated by IAV in different cell types may act as early detection markers or broad-spectrum antiviral targets.

Highlights

Influenza A virus (IAV) infection causes severe respiratory symptoms and persistent morbidity as well as mortality during annual seasonal or pandemic outbreaks, resulting in a severe threat to public health and safety, and even huge economic burden [1]
To further identify whether the mRNA expression of these genes had the same expression pattern in different subtypes of influenza virus infection, the databases with the other subtypes of influenza virus were analyzed and the result showed that the mRNA expression of 11 overlapped genes (IFI6, Interferon-induced protein with tetratricopeptide repeats 2 (IFIT2), ISG15, HERC5, RSAD2, GBP1, IFIT3, IFITM1, LAMP3, USP18, and CXCL10) were remarkably upregulated in A549 cells infected with A/Puerto Rico/8/1934 (H1N1), H5N2, H5N3, and H9N2 (Figure 1B) compared with mock, respectively
These results indicated that IFI6, IFIT2, ISG15, HERC5, RSAD2, GBP1, IFIT3, IFITM1, LAMP3, USP18, and CXCL10 might play key roles in IAV infection

Summary

INTRODUCTION

Influenza A virus (IAV) infection causes severe respiratory symptoms and persistent morbidity as well as mortality during annual seasonal or pandemic outbreaks, resulting in a severe threat to public health and safety, and even huge economic burden [1]. Microarray technology with maturity is a powerful tool for the global view of gene expression levels, and enormous amounts of genome-wide gene expression microarray studies were distributed and archived in the gene expression omnibus (GEO) repository at the National Centre for Biotechnology Information (NCBI) in the last few decades, providing the chance for investigators revisiting these data to solve scientific questions. In this current study, we collected various transcriptomic datasets that were involved in diverse types of cells infected with subtypes of IAV, in order to examine common aspects of host cell responses to various subtypes of IAV infection. By integrating the global gene expression data, our results suggested that the differentially expressed genes involved in host responses might not conform, the similar immune responses of diverse cell types were triggered by the infection of different subtypes of IAV

MATERIALS AND METHODS

RESULTS

SampleType mock

DISCUSSION