Exploring COVID-19 pathogenesis on command-line: A bioinformatics pipeline for handling and integrating omics data

Area of Science:

• Bioinformatics
• Genomics
• Proteomics

Background:

• Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a significant global health threat.
• Omics techniques are crucial for understanding virus mechanisms and impact.
• Bioinformatics expertise is essential for processing and interpreting omics data.

Purpose of the Study:

• To present a robust, open-access computational pipeline for analyzing quantitative proteomics and transcriptomics data.
• To integrate and compare omics data for a comprehensive understanding of SARS-CoV-2 infection.
• To identify molecular markers distinguishing infected from healthy individuals.

Main Methods:

• Development of a computational pipeline from raw omics data to differentially expressed genes.
• Integration and comparison of proteomics and transcriptomics data using Bioconductor packages.
• Exploration of biological processes and pathways associated with mapped transcripts and proteins.

Main Results:

• Increased activity in cholesterol metabolism, immune system, extracellular matrix (ECM), and proteasomal degradation pathways in infected patients.
• Overrepresentation of leukocyte activation profiles in both proteomics and transcriptomics data.
• Identification of a panel of proteins and transcripts consistently regulated in lung transcriptome and plasma proteome, validated in an independent cohort.

Conclusions:

• The presented bioinformatics pipeline effectively extracts and integrates omics information for SARS-CoV-2 research.
• Key pathways and molecular signatures associated with SARS-CoV-2 infection were identified.
• A validated panel of biomarkers can distinguish between healthy and infected individuals, demonstrating the pipeline's utility.