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A Functional Genomics-pharmacotranscriptomics Framework Identifies Host-directed Anti-influenza Agents

ABSTRACT: Influenza A virus (IAV) is a pervasive pathogen of humans, poultry, and livestock, posing an ongoing threat to global health and economic stability. The effectiveness of available antiviral drugs is increasingly compromised by the rapid evolution of drug-resistant IAV strains, highlighting the urgent need for new therapeutic strategies. Here, we present an integrative host-directed drug discovery framework that combines functional genomics and pharmacotranscriptomics to systematically identify compounds with anti-IAV potential. We first aggregated published genome-wide screens to assign each host gene a quantitative functional score reflecting its role in promoting or restricting IAV replication. These scores were then paired with gene expression profiles to estimate the overall antiviral status of host cells. Using large-scale pharmacotranscriptomic data, we screened nearly 20,000 drug-induced transcriptional signatures to identify compounds that shift host gene expression toward an antiviral state. Of 27 top candidates selected for validation, two compounds, lithocholic acid and ALW-II-49-7, not only inhibited IAV replication in vitro but also protected mice from lethal infection in vivo. By shifting the focus from viral to host targets, our approach offers a systematic and scalable path to discover antivirals that are less vulnerable to resistance and may be generalizable to other rapidly mutating pathogens.

ORGANISM(S): Mus musculus

PROVIDER: GSE313921 | GEO | 2026/06/28

REPOSITORIES: GEO

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Project description:Classical antiviral therapy inhibit viral proteins and are subject to resistance. To counteract this emergence, alternative strategy has been developed that target cellular factors. We hypothesized that such approach could also be useful to identify broad antivirals. Influenza A virus was used as a model for viral diversity and need for therapy against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection with different influenza A virus subtypes which could help to identify potential antiviral drugs with broad spectrum. Cellular gene expression response to infection with five different human and avian influenza viruses strains was analyzed and 300 genes were determined as differentially expressed between infected and non-infected samples. Strikingly, only a few genes were induced by infection and related to immune response. A more concise list was used to screen connectivity map, a database of drug-associated gene expression profiles, for molecules with inverse profiles than the signature of infection. We hypothesized that such compounds would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified, and six inhibited influenza viral growth in vitro. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five of the eight identified molecules, demonstrating that this strategy could help to identify broad spectrum antivirals. This is the first study showing that a gene expression based-screening can be used to identify antivirals. Such approaches could accelerate the drug discovery progress and could be extended to other pathogens. A549 (human lung epithelial cells) were infected with 5 different influenza A strains (A/New Caledonia/20/99 (H1N1), A/Moscow/10/99 (H3N2), A/Lyon/969/09 (H1N1 SOI-V), A/Turkey/582/2006 (H5N1), A/Finch/England/2051/94 (H5N2), and A/Chicken/Italy/2076/99 (H7N1)) or mock infected. Five independant replicates were done and hybridized on a different microarray. The overall design is thus composed of 5 mock samples, and 5x5 infected samples.

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A Functional Genomics-pharmacotranscriptomics Framework Identifies Host-directed Anti-influenza Agents

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