SVAtlas: a comprehensive single extracellular vesicle omics resource
Zhongkai Wei, Na Zhou, Ming Jing, Yanling Cai, Yingxin Zhang, Xinyu Wang, Linxinyu Wang, Di Wu, Fuzhong Xue, Qingzhen Hou
Abstract
Extracellular vesicles (EVs) are nanoscale particles released by cells, carrying proteins, nucleic acids, lipids, and metabolites. These vesicles mediate intercellular communication and modulate disease progression across various conditions. Owing to their molecular heterogeneity and the stable bilayer protecting their cargo, EVs serve as valuable tools for early disease detection and personalized therapies. However, traditional bulk EV studies aggregate data, which can mask the distinct molecular profiles of individual EVs critical for targeted diagnostics and treatments, diminishing diagnostic precision. Recent advances in single-EV analysis, leveraging high-resolution sequencing and imaging technologies, have revealed unique molecular signatures. However, a comprehensive database integrating multi-omics data from single EVs remains lacking. To address this, we developed SVAtlas, the first database dedicated to integrating single-EV datasets (2015-2025). SVAtlas incorporates 8120 protein entries, 106 RNA entries (miRNA, mRNA, circRNA, and lncRNA), 2 DNA entries, and 8 lipid/metabolite entries across 276 EV projects, spanning 31 diseases, 32 tissues/organs, and 10 biofluids from five species. SVAtlas offers single-EV datasets with experimental parameters, heterogeneity analyses, disease-specific marker exploration, built-in analysis/clustering/visualization pipelines, and an LLM-based question-answering tool, empowering researchers to explore single-EV omics in detail. Free and accessible at https://www.svatlas.org/, SVAtlas accelerates the clinical translation of single-EV analysis and biomarker discovery.