Measurement of Nitric Oxide Production in Mouse Tracheal Epithelial Cell Cultures Differentiated at the Air Liquid Interface
Abstract
ABSTRACT Airway ciliary dysfunction often leads to impaired mucociliary clearance, a defect frequently associated with dysregulation of canonical nitric oxide (NO) signaling. Indeed, many airway diseases exhibit aberrant levels of exhaled NO, a feature commonly used as a diagnostic indicator in patients. While this measurement is routinely performed clinically, there is currently no validated approach to assess NO release from airway ciliated cells in vitro, limiting mechanistic studies of NO regulation and function. An established method to study airway diseases in vitro is the use of cultured mouse tracheal epithelial cells (MTECs) differentiated at the air–liquid interface (ALI). Here, using this model, we develop a protocol to measure NO released from ciliated cells and accumulated in apical mucus, collected from the ALI-differentiated cultures. Using established instrumentation for NO analysis and a triiodide-based assay, we quantify nitrite, a stable NO metabolite and biomarker of NO production. For assay validation, cells were treated with the NO donor Diethylenetriamine NONOate (DETA-NONOate or DETA/NO) or the NO synthase inhibitor N(ω)-Nitro-L-arginine methyl ester (L-NAME). Together, these approaches demonstrate that this method reliably detects NO in samples from ALI-differentiated airway epithelia, providing an accurate in vitro platform to quantify NO release and model diseases associated with abnormal NO metabolism. SUMMARY The goal of this current protocol is to describe a cell culture-based method to study airway diseases associated with altered nitric oxide (NO) signaling. This method describes the quantification of NO in airway epithelia differentiated at the air-liquid interface (ALI) using a triiodide-based chemiluminescence assay.
Fields of Study & Subjects
Cystic Fibrosis Research Advances
Nitric Oxide and Endothelin Effects
Asthma and respiratory diseases
Publication details
- Journal / source
- Journal of Visualized Experiments
- Issue
- 233
- Publication date
- 3 July 2026
- Language
- EN