A new tool developed by Helmholtz Munich, the German Center for Diabetes Research, and the University of Bonn simplifies the application of spatial proteomics and lipidomics - without any programming knowledge required. With C-COMPASS, scientists can precisely analyze where proteins and lipids are located within cells and how these patterns change under the influence of diseases or other factors. By removing technical barriers, the software makes “spatial omics” accessible to a wider circle of researchers.
Previous tools in spatial proteomics were often inadequate because they could neither precisely record multiple localizations of proteins nor reliably quantify their distribution across different cell compartments. In addition, technical barriers to entry, such as a lack of user interfaces and the need for programming skills, made it difficult to use. Lipidomics has also lacked practical solutions for subcellular localization.
C-COMPASS closes this gap: Using neural networks, the software predicts multiple subcellular protein localizations and combines this information with total proteome data to analyze protein distributions and organelle frequency. The integrated workflow and user-friendly interface facilitate reproducible analyses—even for researchers without programming skills.
The team used C-COMPASS to study proteins in humanized liver tissue under various metabolic conditions. Combining this with lipidome data enabled spatial lipidomics for the first time: lipids were localized using reference maps derived from proteome data. This made it possible to identify changes in lipid distribution in metabolic disorders.
In the future, C-COMPASS will be applied to additional data sets and expanded to include additional omics methods such as spatial transcriptomics in order to capture dynamic cellular processes even more comprehensively.