Temporal transcriptomics identifies early-response and infection-condition-specific modules guiding host-directed anti-EBOV therapeutics

Ebola virus (EBOV) is among the most lethal human pathogens, yet effective treatment options remain limited. While extensive efforts have elucidated the functions of viral proteins, the temporal orchestration of host transcriptional responses-and their exploitation by EBOV during infection-remains poorly defined. Here, we performed integrated time-series transcriptomic profiling using both RNA-seq and microarray analyses to characterize dynamic host and viral gene expression. Through the combination of co-expression network construction and causal inference modeling, we reconstructed the sequential activation of viral and host genes across distinct phases of infection. Our findings show that EBOV induces only minimal transcriptional perturbations during early infection but extensively reprograms host gene expression at later stages, forming infection-specific co-expression modules enriched for antiviral signaling, immune regulation, and stress responses. To prioritize functional host factors, we integrated transcriptional modules with virus-host protein-protein interaction networks and gene-drug databases. This approach identified early-induced host genes with known or predicted interactions with EBOV proteins and pharmacologically actionable targets. RNA interference-mediated silencing of three key regulatory genes (RELB, LDLR, and MYC) significantly impaired EBOV RNA replication and progeny virus production. Furthermore, pharmacological screening identified sorafenib and thioguanine as effective inhibitors of EBOV replication, with EC₅₀ values of 1.529 μM and 2.469 μM, respectively. Collectively, our study uncovers temporally resolved host regulatory programs hijacked by EBOV and demonstrates the utility of integrating dynamic transcriptomics with systems biology, functional validation, and drug screening to identify host-targeted antivirals. These findings provide a conceptual and methodological framework for developing host-targeted therapies against highly pathogenic viruses.IMPORTANCEEbola virus is a devastating pathogen with limited treatment options. A major challenge in developing therapies is understanding how the virus dynamically hijacks our cells over time. This study provides a time-resolved map of the host transcriptional landscape during Ebola virus infection. We reveal that the virus causes minimal early changes but extensively reprograms human gene expression later, creating specific co-expression networks that are essential for viral replication. By integrating these networks with virus-host interaction data, we identified key human genes and demonstrated that silencing them impairs viral replication. Furthermore, we repurposed existing drugs, identifying sorafenib and thioguanine as effective inhibitors. Our work uncovers the temporal strategy of Ebola virus and establishes a framework for discovering host-directed therapies against this and other highly pathogenic viruses.