Gene network inference from single-cell omics data and domain knowledge for constructing COVID-19-specific...

Area of Science:

• Molecular Biology
• Virology
• Immunology

Background:

• Intercellular Adhesion Molecule 1 (ICAM-1) is crucial for cell interactions and implicated in viral transmission (HIV-1, HTLV-1).
• SARS-CoV-2 shares features with these viruses, and its cell-to-cell transmission correlates with COVID-19 severity.
• ICAM-1 expression changes in COVID-19 patients, but its associated signaling pathways in this context remain unidentified.

Purpose of the Study:

• To identify unknown ICAM-1-associated signaling pathways in COVID-19.
• To elucidate the mechanism of SARS-CoV-2 cell-to-cell transmission and its link to COVID-19 severity.
• To contribute to the completion of the COVID-19 Disease Map.

Main Methods:

• Gene network inference using single-cell omics data.
• Analysis of coexpressed genes, removing spurious correlations.
• Validation of inferred models using multiple knowledge bases.

Main Results:

• Construction of ICAM-1-associated pathways by integrating data-driven and knowledge-based approaches.
• Identification of two novel pathways: an upstream pathway involving the non-canonical NF-κB pathway and a downstream pathway with integrins and cytoskeleton proteins.
• Reproducibility of known pathways across different cell types and time points.

Conclusions:

• The study successfully identified novel ICAM-1-associated pathways relevant to COVID-19.
• These findings offer insights into SARS-CoV-2 transmission and disease mechanisms.
• The results aid in refining the COVID-19 Disease Map for better understanding and potential therapeutic strategies.