Fabian Coscia
Max Delbrück Center for Molecular Medicine, Berlin, Germany
Ultrasensitive spatial tissue proteomics to assess health and disease
Formalin-fixed and paraffin-embedded (FFPE) tissues represent an invaluable resource for studying molecular mechanisms underlying diseases. The long archival times of FFPE tissue and the fact that proteins are largely stable therein make them ideal analytes for mass spectrometry driven discovery proteomics. Classical approaches have provided averaged descriptions of the disease related proteome and fail to characterize the critical disease promoting cell populations within the complex tissue environment. To address this, we have recently co-developed Deep Visual Proteomics (DVP) for image-guided tissue proteomics. DVP leverages high resolution microscopy and machine learning based image analysis to identify phenotypically distinct cell populations. Cells for proteomic profiling, discovered by supervised or unsupervised machine learning, are isolated in situ by automated laser microdissection and analyzed by ultra-sensitive mass spectrometry. In my presentation, I will provide an overview of our spatial tissue proteomics pipeline, discuss our DVP workflow, as well as future applications of tissue proteomics down to a few or even single cells.
Selected references
- Mund, A., Coscia, F., Kriston, A., Hollandi, R., Kovács, F., Brunner, A.-D., Migh, E., Schweizer, L., Santos, A., Bzorek, M., et al. (2022). Deep Visual Proteomics defines single-cell identity and heterogeneity. Nature Biotechnology 2022, 1–10. https://doi.org/10.1038/s41587-022-01302-5.
- Makhmut, A., Qin, D., Fritzsche, S., Nimo, J., König, J., and Coscia, F. (2023). A framework for ultra-low-input spatial tissue proteomics. Cell Syst 14, 1002-1014.e5. https://doi.org/10.1016/j.cels.2023.10.003.
- Makhmut, A., Qin, D., Hartlmayr, D., Seth, A., and Coscia, F. (2024). An automated and fast sample preparation workflow for laser microdissection guided ultrasensitive proteomics. Molecular & Cellular Proteomics 23, 100750. https://doi.org/10.1016/j.mcpro.2024.100750.
L'organisation de ce séminaire est soutenu par la SFR B2S.