Host Modulators of H1N1 Cytopathogenicity

Abstract

Influenza A virus infects 5–20% of the population annually, resulting in ∼35,000 deaths and significant morbidity. Current treatments include vaccines and drugs that target viral proteins. However, both of these approaches have limitations, as vaccines require yearly development and the rapid evolution of viral proteins gives rise to drug resistance. In consequence additional intervention strategies, that target host factors required for the viral life cycle, are under investigation. Here we employed arrayed whole-genome siRNA screening strategies to identify cell-autonomous molecular components that are subverted to support H1N1 influenza A virus infection of human bronchial epithelial cells. Integration across relevant public data sets exposed druggable gene products required for epithelial cell infection or required for viral proteins to deflect host cell suicide checkpoint activation. Pharmacological inhibition of representative targets, RGGT and CHEK1, resulted in significant protection against infection of human epithelial cells by the A/WS/33 virus. In addition, chemical inhibition of RGGT partially protected against H5N1 and the 2009 H1N1 pandemic strain. The observations reported here thus contribute to an expanding body of studies directed at decoding vulnerabilities in the command and control networks specified by influenza virulence factors.

Meta- and Orthogonal Integration of Influenza “OMICs” Data Defines a Role for UBR4 in Virus Budding

“…To comprehensively survey the repertoire of host cellular factors affecting the replication of IAV, we analyzed the hit lists of eight independent RNAi datasets published previously (Brass et al, 2009; Karlas et al, 2010; König et al, 2010; Shapira et al, 2009; Su et al, 2013; Tran et al, 2013; Ward et al, 2012; Watanabe et al, 2014). A total of 1,257 genes was reported as confirmed host dependency factors and 192 genes as confirmed antiviral factors in at least one of the above-mentioned reports (Figures 1A or 1D, respectively, orange and red innermost circle segments).…”

“…A pair-wise comparison to identify genes in common between screening sets resulted in only a modest overlap: 101 pro-viral and 2 anti-viral genes confirmed by multiple studies (red circle segments and purple inter-gene links in Figures 1A and 1D, respectively). To mitigate the influence of false-negative hit calls due to variances in data analysis methodologies and hit selection, we considered an expanded version of the respective hit lists based on the raw data of previously unpublished activity scores of four genome-wide RNAi screens (Brass et al, 2009; Karlas et al, 2010; König et al, 2010; Ward et al, 2012). We applied a statistical analysis to each screen set, termed the RSA algorithm, that utilizes an iterative accumulative hypergeometric distribution formula (König et al, 2007), to obtain a Z score for each gene in each individual screen (Figure 1, blue circles).…”

“…The innermost circle categorizes the cellular factors into the respective gene status: (1) gene was confirmed in the indicated screen and at least one additional screen (red); (2) gene reported confirmed in only the indicated screen (orange), (3) gene was not reported confirmed in any screen, but displays a high activity (Z score ≤ −2) in the raw datasets of the indicated screen (transparent white). The four blue circles display the calculated Z scores of each host factor (A, B, and C) or restriction factors (D) within four primary raw screen datasets, respectively (from outside to inside: Brass et al, 2009; Karlas et al, 2010; König et al, 2007; Ward et al, 2012). Intensity from white to blue indicates increasing significance of activity (lower Z score).…”

Bioinformatics Analysis of Proteome Changes in Calu-3 Cell Infected by Influenza A Virus (H5N1)

“…Of these genes, TSC1 was reported to be essential for H5N1 to suppress the mTOR signaling and induce autophagic cell death [Ma et al, 2011]. Meanwhile, RRAGD encoded a small G protein which contributes to the amino acid responsiveness of mTOR as a constituent of the 'regulator' [Sancak et al, 2010], and it was speculated that RRAGD was a limiting host factor for viral corruption of mTOR mediation [Ward et al, 2012]. In a word, FAX5 might participate in H5N1 infection by regulating the expression level of genes such as TSC1 or RRAGD .…”

Prolidase Is Required for Early Trafficking Events during Influenza A Virus Entry

“…Genome-wide small interfering RNA (siRNA) screens are a powerful tool to identify host factors associated with viral infections. Several such screens have been performed to determine cellular factors required by IAV during infection (23)(24)(25)(26)(27)(28)(29)(30). Surprisingly, there was hardly any overlap between the primary hits identified in these screens (31).…”