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Background <p>Many respiratory viruses attack the airway epithelium and cause a wide spectrum of diseases for which we have limited therapies. To date, a few primary human stem cell-based models of the proximal airway have been reported for drug discovery but scaling them up to a higher throughput platform remains a significant challenge. As a result, most of the drug screening assays for respiratory viruses are performed on commercial cell line-based 2D cultures that provide limited translational ability.</p> Methods <p>We optimized a primary human stem cell-based mucociliary airway epithelium model of SARS-CoV-2 infection, in 96-well air–liquid-interface (ALI) format, which is amenable to moderate throughput drug screening. We tested the model against SARS-CoV-2 parental strain (Wuhan) and variants Beta, Delta, and Omicron. We applied this model to screen 2100 compounds from targeted drug libraries using a high throughput-high content image-based quantification method.</p> Results <p>The model recapitulated the heterogeneity of infection among patients with SARS-CoV-2 parental strain and variants. While there were heterogeneous responses across variants for host factor targeting compounds, the two direct-acting antivirals we tested, Remdesivir and Paxlovid, showed consistent efficacy in reducing infection across all variants and donors. Using the model, we characterized a new antiviral drug effective against both the parental strain and the Omicron variant.</p> Conclusion <p>This study demonstrates that the 96-well ALI model of primary human mucociliary epithelium can recapitulate the heterogeneity of infection among different donors and SARS-CoV-2 variants and can be used for moderate throughput screening. Compounds that target host factors showed variability among patients in response to SARS-CoV-2, while direct-acting antivirals were effective against SARS-CoV-2 despite the heterogeneity of patients tested.</p>

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Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月16日

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  • Chandani Sen,
  • Tammy M. Rickabaugh,
  • Arjit Vijey Jeyachandran,
  • Constance Yuen,
  • Maisam Ghannam,
  • Abdo Durra,
  • Adam Aziz,
  • Kristen Castillo,
  • Gustavo Garcia Jr.,
  • Arunima Purkayastha,
  • Brandon Han,
  • Felix W. Boulton,
  • Eugene Chekler,
  • Robert Garces,
  • Karen C. Wolff,
  • Laura Riva,
  • Melanie G. Kirkpatrick,
  • Amal Gebara-Lamb,
  • Case W. McNamara,
  • Ulrich A. K. Betz,
  • Vaithilingaraja Arumugaswami,
  • Robert Damoiseaux,
  • Brigitte N. Gomperts

摘要

Background

Many respiratory viruses attack the airway epithelium and cause a wide spectrum of diseases for which we have limited therapies. To date, a few primary human stem cell-based models of the proximal airway have been reported for drug discovery but scaling them up to a higher throughput platform remains a significant challenge. As a result, most of the drug screening assays for respiratory viruses are performed on commercial cell line-based 2D cultures that provide limited translational ability.

Methods

We optimized a primary human stem cell-based mucociliary airway epithelium model of SARS-CoV-2 infection, in 96-well air–liquid-interface (ALI) format, which is amenable to moderate throughput drug screening. We tested the model against SARS-CoV-2 parental strain (Wuhan) and variants Beta, Delta, and Omicron. We applied this model to screen 2100 compounds from targeted drug libraries using a high throughput-high content image-based quantification method.

Results

The model recapitulated the heterogeneity of infection among patients with SARS-CoV-2 parental strain and variants. While there were heterogeneous responses across variants for host factor targeting compounds, the two direct-acting antivirals we tested, Remdesivir and Paxlovid, showed consistent efficacy in reducing infection across all variants and donors. Using the model, we characterized a new antiviral drug effective against both the parental strain and the Omicron variant.

Conclusion

This study demonstrates that the 96-well ALI model of primary human mucociliary epithelium can recapitulate the heterogeneity of infection among different donors and SARS-CoV-2 variants and can be used for moderate throughput screening. Compounds that target host factors showed variability among patients in response to SARS-CoV-2, while direct-acting antivirals were effective against SARS-CoV-2 despite the heterogeneity of patients tested.