Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2
Abstract 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 throug...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12931-025-03095-y |
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| author | Chandani Sen Tammy M. Rickabaugh Arjit Vijey Jeyachandran Constance Yuen Maisam Ghannam Abdo Durra Adam Aziz Kristen Castillo Gustavo Garcia 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 |
| author_facet | Chandani Sen Tammy M. Rickabaugh Arjit Vijey Jeyachandran Constance Yuen Maisam Ghannam Abdo Durra Adam Aziz Kristen Castillo Gustavo Garcia 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 |
| author_sort | Chandani Sen |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-2045ddd67bdc4de488692d091b970997 |
| institution | Kabale University |
| issn | 1465-993X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Respiratory Research |
| spelling | doaj-art-2045ddd67bdc4de488692d091b9709972025-01-19T12:36:33ZengBMCRespiratory Research1465-993X2025-01-0126111410.1186/s12931-025-03095-yOptimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2Chandani Sen0Tammy M. Rickabaugh1Arjit Vijey Jeyachandran2Constance Yuen3Maisam Ghannam4Abdo Durra5Adam Aziz6Kristen Castillo7Gustavo Garcia8Arunima Purkayastha9Brandon Han10Felix W. Boulton11Eugene Chekler12Robert Garces13Karen C. Wolff14Laura Riva15Melanie G. Kirkpatrick16Amal Gebara-Lamb17Case W. McNamara18Ulrich A. K. Betz19Vaithilingaraja Arumugaswami20Robert Damoiseaux21Brigitte N. Gomperts22Department of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Molecular and Medical Pharmacology, University of CaliforniaDepartment of Molecular and Medical Pharmacology, University of CaliforniaDepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Molecular and Medical Pharmacology, University of CaliforniaDepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLADepartment of Molecular and Medical Pharmacology, University of CaliforniaDepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLAEMD SeronoEMD SeronoCalibr-Skaggs Institute for Innovative MedicinesCalibr-Skaggs Institute for Innovative MedicinesCalibr-Skaggs Institute for Innovative MedicinesCalibr-Skaggs Institute for Innovative MedicinesCalibr-Skaggs Institute for Innovative MedicinesMerck KGaADepartment of Molecular and Medical Pharmacology, University of CaliforniaDepartment of Molecular and Medical Pharmacology, University of CaliforniaDepartment of Pediatrics, David Geffen School of Medicine, UCLA Children’s Discovery and Innovation Institute, Mattel Children’s Hospital UCLA, UCLAAbstract 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.https://doi.org/10.1186/s12931-025-03095-yHuman mucociliary epitheliumSARS-CoV-2Respiratory viral infectionsHigh throughput drug screeningAnti-viral screeningSmall-molecules |
| spellingShingle | Chandani Sen Tammy M. Rickabaugh Arjit Vijey Jeyachandran Constance Yuen Maisam Ghannam Abdo Durra Adam Aziz Kristen Castillo Gustavo Garcia 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 Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2 Respiratory Research Human mucociliary epithelium SARS-CoV-2 Respiratory viral infections High throughput drug screening Anti-viral screening Small-molecules |
| title | Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2 |
| title_full | Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2 |
| title_fullStr | Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2 |
| title_full_unstemmed | Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2 |
| title_short | Optimization of a micro-scale air–liquid-interface model of human proximal airway epithelium for moderate throughput drug screening for SARS-CoV-2 |
| title_sort | optimization of a micro scale air liquid interface model of human proximal airway epithelium for moderate throughput drug screening for sars cov 2 |
| topic | Human mucociliary epithelium SARS-CoV-2 Respiratory viral infections High throughput drug screening Anti-viral screening Small-molecules |
| url | https://doi.org/10.1186/s12931-025-03095-y |
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