LION/web: a web-based ontology enrichment tool for lipidomic data analysis

Area of Science:

• Lipidomics
• Bioinformatics
• Systems Biology

Background:

• Lipidomic analyses generate vast datasets, posing challenges for data interpretation and understanding lipid roles in biological systems.
• Existing methods struggle to translate complex lipidomic results into meaningful biological insights.

Purpose of the Study:

• To develop a novel lipid ontology (LION) and a web-based interface (LION/web) for enhanced interpretation of lipidomic data.
• To associate over 50,000 lipid species with detailed biophysical, chemical, and cell biological features.

Main Methods:

• Construction of the LION ontology, linking lipid species to functional attributes.
• Development of LION/web, a web-based tool utilizing enrichment algorithms for lipidome analysis.
• Validation using lipidomic datasets from macrophage subcellular fractions and Chinese hamster ovary cells.

Main Results:

• LION/web successfully identified significant lipid-associated terms in subcellular fractions, distinguishing plasma membranes from microsomes.
• Key terms enriched included "plasma membrane," "glycerophosphoserines," and features related to bilayer thickness and lateral diffusion.
• Analysis of membrane fluidity changes in response to arachidonic acid correlated experimental findings with LION/web term enrichment, including "high lateral diffusion."

Conclusions:

• LION/web demonstrates robust functionality for interpreting complex lipidomic data.
• The tool provides a freely accessible, platform-independent resource for researchers.
• This facilitates a deeper understanding of lipid involvement in biological processes.