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<p>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 <i>Z</i>′ &gt; 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.</p>

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A robust cell-based infection model for Rhinovirus C research and antiviral drug discovery

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月11日

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  • Heyrhyoung Lyoo,
  • Yeranddy A. Alpizar,
  • Céline Sablon,
  • Toon Röpke,
  • Jasmine Paulissen,
  • Madina Rasulova,
  • Nathalie Thys,
  • Chang-Soo Yun,
  • Nam-Chul Cho,
  • Kai Dallmeier,
  • Pieter Leyssen,
  • Soo-Bong Han,
  • Johan Neyts,
  • Hendrik Jan Thibaut

摘要

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.