Discovering Perturbation of Modular Structure in HIV Progression by Integrating Multiple Data Sources Through...

Area of Science:

• Bioinformatics
• Systems Biology
• Molecular Biology

Background:

• Understanding HIV-1 disease progression requires identifying disruptions in human gene modules.
• Stage-specific infection patterns are crucial for therapeutic strategies.

Purpose of the Study:

• To propose a novel methodology for detecting perturbations in human gene modules during HIV-1 infection.
• To integrate multiple biological data sources for a comprehensive analysis.

Main Methods:

• Integration of gene expression, protein-protein interaction (PPI), and gene ontology (GO) information using non-negative matrix factorization (NMF).
• NMF-based clustering to form gene meta-modules.
• Analysis of meta-modular perturbation through topological and intramodular properties, and rank aggregation.
• Assessment of GO term preservation and coregulation patterns of transcription factors (TFs).

Main Results:

• Successfully integrated diverse biological data into robust meta-modules.
• Identified significant perturbations in meta-modular structure correlating with HIV-1 progression stages.
• Revealed changes in gene expression patterns, PPI networks, and functional similarities.
• Analyzed the preservation of GO terms and dynamic changes in TF coregulation.

Conclusions:

• The proposed methodology effectively detects disruptions in human gene modules during HIV-1 infection.
• This approach provides insights into stage-specific viral infection patterns.
• The findings contribute to a better understanding of HIV-1 pathogenesis at a systems level.