Predicting Influenza and Rhinovirus Infections in Airway Cells Utilizing Volatile Emissions.

Abstract

Respiratory viral infections are common and potentially devastating to patients with underlying lung disease. Diagnosing viral infections often requires invasive sampling, and interpretation often requires specialized laboratory equipment. Here, we test the hypothesis that a breath test could diagnose influenza and rhinovirus infections using an in vitro model of the human airway. Cultured primary human tracheobronchial epithelial cells were infected with either influenza A H1N1 or rhinovirus 1B and compared with healthy control cells. Headspace volatile metabolite measurements of cell cultures were made at 12-hour time points postinfection using a thermal desorption-gas chromatography-mass spectrometry method. Based on 54 compounds, statistical models distinguished volatile organic compound profiles of influenza- and rhinovirus-infected cells from healthy counterparts. Area under the curve values were 0.94 for influenza, 0.90 for rhinovirus, and 0.75 for controls. Regression analysis predicted how many hours prior cells became infected with a root mean square error of 6.35 hours for influenza- and 3.32 hours for rhinovirus-infected cells. Volatile biomarkers released by bronchial epithelial cells could not only be used to diagnose whether cells were infected, but also the timing of infection. Our model supports the hypothesis that a breath test could serve to diagnose viral infections.