SVAtlas: a comprehensive single extracellular vesicle omics resource

Area of Science:

• Biochemistry
• Molecular Biology
• Genomics

Background:

• Extracellular vesicles (EVs) mediate intercellular communication and are crucial in disease.
• Single-EV analysis offers higher precision than bulk studies but lacks integrated data.
• Existing methods mask unique molecular signatures essential for targeted diagnostics.

Purpose of the Study:

• To develop the first comprehensive database integrating multi-omics data from single EVs.
• To provide a resource for exploring EV heterogeneity and disease-specific markers.
• To facilitate the clinical translation of single-EV analysis.

Main Methods:

• Development of SVAtlas, a database integrating single-EV datasets from 2015-2025.
• Inclusion of protein, RNA, DNA, lipid, and metabolite data from 276 EV projects.
• Incorporation of experimental parameters, heterogeneity analyses, and analysis pipelines.

Main Results:

• SVAtlas integrates 8120 protein, 106 RNA, 2 DNA, and 8 lipid/metabolite entries.
• The database covers 31 diseases, 32 tissues, 10 biofluids, and five species.
• Includes an LLM-based QA tool for detailed exploration of single-EV omics data.

Conclusions:

• SVAtlas is a unique resource for single-EV multi-omics research.
• The database empowers researchers to explore EV heterogeneity and identify biomarkers.
• SVAtlas promotes accelerated clinical translation of EV-based diagnostics and therapies.