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Related Concept Videos

Proteomics01:33

Proteomics

8.0K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
8.0K

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Deep Visual Proteomics defines single-cell identity and heterogeneity.

Andreas Mund1, Fabian Coscia2,3, András Kriston4,5

  • 1Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. andreas.mund@cpr.ku.dk.

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Deep Visual Proteomics (DVP) links cell images to protein levels, enabling single-cell proteomic analysis. This method reveals spatial proteome changes during melanoma progression, aiding clinical sample analysis.

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Area of Science:

  • Proteomics
  • Biotechnology
  • Cancer Research

Background:

  • Spatial proteomics methods struggle to link imaging with single-cell protein data.
  • A gap exists in connecting cellular phenotypes to precise protein abundance at the single-cell level.

Purpose of the Study:

  • Introduce Deep Visual Proteomics (DVP) to bridge imaging and single-cell spatial proteomics.
  • Link cellular phenotypes to protein abundance while maintaining spatial context.
  • Analyze proteomic changes in melanoma progression.

Main Methods:

  • Combined AI-driven image analysis of cellular phenotypes with laser microdissection and mass spectrometry.
  • Automated single-cell/nucleus isolation for proteomic profiling.
  • Applied DVP to cell cultures and archived melanoma tissue.

Main Results:

  • Classified distinct cell states and their proteomic profiles.
  • Identified spatially resolved proteome changes during melanoma progression.
  • Revealed altered mRNA splicing, reduced interferon signaling, and antigen presentation in metastatic melanoma.

Conclusions:

  • DVP successfully links cellular phenotypes to spatial proteomic data at single-cell resolution.
  • DVP provides insights into cancer progression pathways.
  • DVP has significant implications for molecular profiling of clinical samples.