![[feed]](/style/images/feed-icon-14x14.png){kind=icon}
Tools
Tools
Preview |
PDF (Original Article)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
19MB |
![[thumbnail of Supplementary Information]](https://edoc.mdc-berlin.de/style/images/fileicons/other.png) |
Other (Supplementary Information)
72MB |
| Item Type: | Article |
|---|---|
| Title: | Deep Visual Proteomics defines single-cell identity and heterogeneity |
| Creators Name: | Mund, A., Coscia, F., Kriston, A., Hollandi, R., Kovács, F., Brunner, A.D., Migh, E., Schweizer, L., Santos, A., Bzorek, M., Naimy, S., Rahbek-Gjerdrum, L.M., Dyring-Andersen, B., Bulkescher, J., Lukas, C., Eckert, M.A., Lengyel, E., Gnann, C., Lundberg, E., Horvath, P. and Mann, M. |
| Abstract: | Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples. |
| Keywords: | Laser Capture Microdissection, Mass Spectrometry, Melanoma, Proteome, Proteomics |
| Source: | Nature Biotechnology |
| ISSN: | 1087-0156 |
| Publisher: | Nature Publishing Group |
| Volume: | 40 |
| Number: | 8 |
| Page Range: | 1231-1240 |
| Date: | August 2022 |
| Official Publication: | https://doi.org/10.1038/s41587-022-01302-5 |
| PubMed: | View item in PubMed |
Repository Staff Only: item control page
