Stephen Mackay
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Stephen Mackay has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Jennifer S. Guimbellot
Gregory Fleming James Cystic Fibrosis Research Center University of Alabama at Birmingham Birmingham Alabama USA
1 shared publication - Johnathan Bailey
Department of Pediatrics, Division of Pulmonary and Sleep Medicine, UAB, Birmingham, AL 35233, USA
1 shared publication - Justin D. Anderson
Affiliations Department of Pediatrics, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America, Gregory Fleming James Cystic Fibrosis Research Center, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
1 shared publication - Latona Kersh
Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham (UAB), Birmingham, AL 35294, USA
1 shared publication - Lily Deng
Department of Pediatrics, Division of Pulmonary and Sleep Medicine, UAB, Birmingham, AL 35233, USA
1 shared publication - Steven Mark Rowe
Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham, USA
1 shared publication
Latest Publications
- Open Access
Human Nasal Epithelial Organoids for Therapeutic Development in Cystic Fibrosis
We describe a human nasal epithelial (HNE) organoid model derived directly from patient samples that is well-differentiated and recapitulates the airway epithelium, including the expression of cilia, mucins, tight junctions, the cystic fibrosis transmembrane conductance regulator (CFTR), and ionocytes. This model requires few cells compared to airway epithelial monolayer cultures, with multiple outcome measurements depending on the application. A novel feature of the model is the predictive capacity of lumen formation, a marker of baseline CFTR function that correlates with short-circuit current activation of CFTR in monolayers and discriminates the cystic fibrosis (CF) phenotype from non-CF. Our HNE organoid model is amenable to automated measurements of forskolin-induced swelling (FIS), which distinguishes levels of CFTR activity. While the apical side is not easily accessible, RNA- and DNA-based therapies intended for systemic administration could be evaluated in vitro, or it could be used as an ex vivo biomarker of successful repair of a mutant gene. In conclusion, this highly differentiated airway epithelial model could serve as a surrogate biomarker to assess correction of the mutant gene in CF or other diseases, recapitulating the phenotypic and genotypic diversity of the population.
Open AccessHuman Nasal Epithelial Organoids for Therapeutic Development in Cystic Fibrosis
We describe a human nasal epithelial (HNE) organoid model derived directly from patient samples that is well-differentiated and recapitulates the airway epithelium, including the expression of cilia, mucins, tight junctions, the cystic fibrosis transmembrane conductance regulator (CFTR), and ionocytes. This model requires few cells compared to airway epithelial monolayer cultures, with multiple outcome measurements depending on the application. A novel feature of the model is the predictive capacity of lumen formation, a marker of baseline CFTR function that correlates with short-circuit current activation of CFTR in monolayers and discriminates the cystic fibrosis (CF) phenotype from non-CF. Our HNE organoid model is amenable to automated measurements of forskolin-induced swelling (FIS), which distinguishes levels of CFTR activity. While the apical side is not easily accessible, RNA- and DNA-based therapies intended for systemic administration could be evaluated in vitro, or it could be used as an ex vivo biomarker of successful repair of a mutant gene. In conclusion, this highly differentiated airway epithelial model could serve as a surrogate biomarker to assess correction of the mutant gene in CF or other diseases, recapitulating the phenotypic and genotypic diversity of the population.