BackgroundInnate immune responses are fine-tuned by small noncoding RNA molecules termed microRNAs (miRs) that modify gene expression in response to the environment. During acute infections, miRs can be secreted in extracellular vesicles (EV) to facilitate cell-to-cell genetic communication. The purpose of this study was to characterize the baseline population of miRs secreted in EVs in the airways of young children (airway secretory microRNAome) and examine the changes during rhinovirus (RV) infection, the most common cause of asthma exacerbations and the most important early risk factor for the development of asthma beyond childhood.MethodsNasal airway secretions were obtained from children (≤3 yrs. old) during PCR-confirmed RV infections (n = 10) and age-matched controls (n = 10). Nasal EVs were isolated with polymer-based precipitation and global miR profiles generated using NanoString microarrays. We validated our in vivo airway secretory miR data in an in vitro airway epithelium model using apical secretions from primary human bronchial epithelial cells (HBEC) differentiated at air-liquid interface (ALI). Bioinformatics tools were used to determine the unified (nasal and bronchial) signature airway secretory miRNAome and changes during RV infection in children.ResultsMultiscale analysis identified four signature miRs comprising the baseline airway secretory miRNAome: hsa-miR-630, hsa-miR-302d-3p, hsa- miR-320e, hsa-miR-612. We identified hsa-miR-155 as the main change in the baseline miRNAome during RV infection in young children. We investigated the potential biological relevance of the airway secretion of hsa-mir-155 using in silico models derived from gene datasets of experimental in vivo human RV infection. These analyses confirmed that hsa-miR-155 targetome is an overrepresented pathway in the upper airways of individuals infected with RV.ConclusionsComparative analysis of the airway secretory microRNAome in children indicates that RV infection is associated with airway secretion of EVs containing miR-155, which is predicted in silico to regulate antiviral immunity. Further characterization of the airway secretory microRNAome during health and disease may lead to completely new strategies to treat and monitor respiratory conditions in all ages.