← BioTransfer GEO Dataset Finder
GEO series

Characterizing spatial and global host innate immune responses against SARS-CoV-1 and -2 infection in pathologically relevant human lung epithelial cells

GSE255647 Homo sapiens Expression profiling by high throughput sequencing 27 samples 2025/02/05 GPL21697
Summary
Severe acute respiratory syndrome coronavirus-1 (SARS-CoV-1) and -2 (SARS-CoV-2) are beta-coronaviruses (β-CoVs) that have caused significant morbidity and mortality worldwide. Therefore, a better understanding of host responses to β-CoVs would provide insights into the pathogenesis of these viruses to identify potential targets for medical countermeasures. Our objective is to use a systems biology approach to explore the magnitude and scope of innate immune responses triggered by SARS-CoV-1 and -2 infection over time in pathologically relevant human lung epithelial cells (Calu-3/2B4 cells). Total RNA extracted at 12, 24, and 48 hours after β-CoVs infection of Calu-3/2B4 cells were subjected to RNA sequencing, bioinformatics, and functional enrichment analysis to select genes whose expressions were significantly modulated upon infection over time. The results of our study demonstrate that SARS-CoV-1 and -2 stimulate similar yet distinct innate antiviral signaling pathways in pathologically relevant human lung epithelial cells. Upregulated genes found at multiple time points regulated the viral life cycle, interferons, and interferon-stimulated genes (ISGs). Based on their profound modulation upon infection, we selected four ISGs, i.e., bone marrow stromal cell antigen 2 (BST2), Z-DNA Binding Protein 1 (ZBP1), C-X-C Motif Chemokine Ligand 11 (CXCL11), and Interferon Induced Transmembrane Protein 1 (IFITM1) for characterization as potential drug targets against β-CoVs.
Download
NCBI GEO page ↗ Paper (PMID 39874350) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.