Gene expression data of human airway epithelium following human parechoviruses infection

Human parechoviruses (HPeVs), a poorly studied genus within the Picornaviridae family, are classified into 19 genotypes of which HPeV1 and HPeV3 are the most often detected. HPeVs pathogenesis is poorly understood as there are no animal models and the previous studies have only been conducted in immortalized monolayer cell cultures which do not adequately represent the characteristics of human tissues. To bridge this gap, we determined the polarity of infection, replication kinetics, and cell tropism of HPeV1 and HPeV3 in the well-differentiated human airway epithelial (HAE) model. We found the HAE cultures to be permissive for HPeVs. We speculated that differences in the airway epithelium host response may contribute to the distinct clinical outcomes and performed transcriptome analyses to compare the HAE gene expression profiles induced by HPeV1 and HPeV3 infection. Transcriptional profiling suggested that HPeV3 infection induced stronger immune activation than HPeV1. The polarized entry and genotype-specific host responses may contribute to the differences into the pathogenesis and clinical outcomes associated with HPeV1 and HPeV3. HAE (donor 59701) cultures in five technical replicates were basolaterally inoculated with HPeV1 or HPeV3 (or mock). Cultures were lysed and RNA extracted by High Pure RNA Isolation Kit (Roche LifeScience, Penzberg, Germany) 72hrs post-infection. RNA samples concentration and quality was determined by Nanodrop (ThermoFisher Scientific) and BioAnalyzer (Agilent Technologies, Santa Clara, California). Total RNA samples were labeled and hybridized using the Human Clariom S HT microarray platform according to the manufacturer’s guidelines (Affymetrix/ThermoFisher Scientific). The BrainArray (version 22) custom Chip Description File (CDF) was used to re-map probesets on the arrays based on the latest genome and transcriptome information. Probesets normalization was achieved by Robust Multi-array Average (RMA) function in the R programming environment.