Key result
High-content imaging establishes a robust high-throughput infection system for Rhinovirus C antiviral drug discovery.
Why the study?
Progress in RV-C research and drug discovery has been limited by the lack of robust, scalable cell-based infection models that recapitulate the complete RV-C replication cycle.
The development of a robust, scalable high-content imaging-based infection model for Rhinovirus C enables high-throughput screening for novel antiviral drugs.
Answers are grounded in this paper and cite their sources.
Scalable RV-C cell model may accelerate antiviral discovery for severe respiratory illness; validation studies needed before clinical translation.
Rhinoviruses (RV) comprise three species, RV-A, RV-B, and RV-C, with approximately 170 types. RV-C is associated with severe respiratory illness, particularly in children and individuals with asthma or chronic obstructive pulmonary disease, underscoring the need for effective antiviral strategies. Progress in RV-C research and drug discovery has been limited by the lack of robust, scalable cell-based infection models that recapitulate the complete RV-C replication cycle. Here, we describe a high-content imaging (HCI)-based high-throughput infection system for RV-C. Rather than relying solely on receptor overexpression, we used a genetically stable fluorescent reporter virus (RV-C15a-mGL) to screen ~300 monoclonal cell lines expressing the RV-C receptor variant CDHR3-Tyr529. This approach identified a clone that efficiently supports RV-C replication and revealed that productive infection depends on determinants beyond receptor abundance alone. Using this clone, we established and validated a robust, scalable screening platform with Z' > 0.75 in both 96- and 384-well formats. The system was readily adapted to additional RV-C types (C11 and C41), as well as RV-A and RV-B. A pilot screen of approximately 10,000 small molecules identified both known and novel RV-C inhibitors, supporting the utility of this platform for antiviral discovery and for advancing the study of RV-C biology.
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Lyoo et al. (2026) studied Rhinovirus C infection. High-throughput screening platform (RV-C15a-mGL reporter virus in HeLa-CDHR3C529Y cells) was evaluated on Assay robustness (Z'-factor). A robust, scalable high-content imaging-based high-throughput infection system for Rhinovirus C was established, achieving a Z′ > 0.75 in both 96- and 384-well formats for antiviral drug discovery.
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