A. Mund, F. Coscia, A. Kriston, R. Hollandi, F. Kovács, A.-D. Brunner, E. Migh, L. Schweizer, A. Santos, M. Bzorek, S. Naimy, L.M. Rahbek-Gjerdrum, B. Dyring-Andersen, J. Bulkescher, C. Lukas, M.A. Eckert, E. Lengyel, C. Gnann, E. Lundberg, P. Horvath, M. Mann:
Deep Visual Proteomics defines single-cell identity and heterogeneity
Nature Biotechnology (2022) vol. 40, pp.1231–1240
By individually excising nuclei from cell culture, distinct cell states can be classified 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 signalling 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.
For this research, cells or nuclei were excised using a LMD7 laser microdissection microscope which was adapted for automated single-cell automation .