ERJ Open ResearchMicrobiologyPeer-reviewed journal article
Donor-derived airway ALI model for high-throughput screening of antiviral combinations with concurrent analysis of antiviral efficacy and epithelial toxicity using ciliR
Daniela Cardinale, Oriane GrantiD, Dani Do Hyang LeeiD, Samuel EllisiD, Robert E. HyndsiD, Richard M. AngelliD, Christopher O’CallaghaniD, Mario Cortina‐BorjaiD, Elaine Thomas, Claire Mary SmithiD
Abstract
Respiratory RNA viral infections significantly impact quality of life and productivity, both in terms of pandemics (e.g., SARS-CoV-2, influenza A viruses) and seasonal infections such as respiratory syncytial virus (RSV). Globally, RSV causes an estimated 33.8 million cases annually in children under five, leading to 2.8-4.3 million hospital admissions and up to 199,000 deaths. Human-relevant drug screening models are key to addressing the urgent need for effective antiviral treatments for RSV, particularly in vulnerable patient groups. Here, we present a donor-derived differentiated primary human nasal epithelial cell, 96-HTS Transwell air-liquid interface (ALI) model designed to investigate the effects of combination antiviral therapies on RSV infection in primary human ciliated airway epithelium. Additionally, we describe novel analytical tools using R (ciliR) to screen drug combinations by concurrently measuring efficacy and ciliary beat frequency as a sensitive marker of cell toxicity. Our results demonstrate that the smaller 96-HTS ALI cultures retain comparable epithelial composition and ciliary function to conventional ALI culture formats. These cultures are permissible to infection with an RSV-GFP reporter virus, enabling quantitative comparison and combination treatment across multiple epithelial cultures from the same donor. We anticipate that our disease-relevant system will serve as a foundation for larger-scale experiments aimed at optimizing combination therapy for RSV and other respiratory viruses.
- organism: human
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- approach: experimental assay
- Citations
- 4
- FWCI
- 18.73
- Field percentile
- top 1%
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