Characterizing immune signatures of seasonal coronaviruses HCoV-229E and -OC43 in human nasal airway epithelial cells

Seasonal coronaviruses, including HCoV-229E, -NL63, -OC43, and -HKU1, are prevalent worldwide, predominantly causing mild, self-limiting upper respiratory (re-)infections in adults, often presenting as the common cold. However, in individuals with compromised immune systems, these viruses may lead to more severe illness and even fatalities. Recently, there has been a renewed interest in studying HCoVs due to their amenability to handling in reduced biosafety containment, offering valuable alternatives to SARS-CoV-2 for preclinical screening and the development of antiviral treatments. Despite their significance, research on HCoVs has been hindered by limited host-genomic data. To address this, we performed RNA-sequencing on 3D air-liquid interface human nasal airway epithelial cells (hNECs) infected with the alphacoronavirus HCoV-229E and the betacoronavirus HCoV-OC43. These hNECs were derived from pooled adult donors and exhibited pseudostratified mucociliated differentiation, faithfully replicating the complexities of normal airway biology. Our study aimed to identify specific immune signatures associated with HCoV infections in a physiologically relevant model. By elucidating the host responses induced by different seasonal coronaviruses, we can gain valuable insights into their pathogenesis and interactions with the respiratory epithelium. This knowledge may pave the way for the development of targeted therapeutics and prophylactics to combat HCoV infections effectively. In this study, we aimed to investigate variations in gene expression among different human coronaviruses (HCoV). To achieve this, primary human nasal epithelial cells (hNECs) were subjected to single infections with HCoV-229E, and -OC43 at a multiplicity of infection (MOI) of 0.01, while another group remained uninfected, all maintained at 33°C. RNA samples were collected from both uninfected and virus-infected hNECs at 24 and 72 hours post-infection to assess gene expression changes. The RNA samples' quality and integrity were evaluated using the Agilent 2100 Bioanalyzer (Agilent Technologies) before proceeding with library preparation. Strand-specific RNA-sequencing was performed at Novogene (Cambridge, UK). Subsequently, FASTQ files were processed using Partek Flow to obtain reliable data for downstream analysis. Differentially expressed genes were identified by applying stringent criteria, including statistical significance (P < 0.005) and fold change (>2), utilizing two replicates for each condition. By comparing the gene expression patterns, we aimed to uncover the pathways impacted by viral infections. This comprehensive examination of gene expression differences among HCoV strains in hNECs will provide valuable insights into the molecular responses of respiratory epithelial cells to different coronaviruses, potentially contributing to the development of targeted therapeutic strategies.