Cited by 176Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsSingle-cell and spatial transcriptomics

Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome

Open access
Rosenberger, Florian A., Thielert, Marvin, Strauss, Maximilian T., Schweizer, Lisa, Ammar, Constantin, Mädler, Sophia C., Metousis, Andreas, Skowronek, Patricia +9 more·2023·Nature Methods

Abstract

Single-cell proteomics by mass spectrometry is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed mass spectrometry. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a cell slice. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics and spatial omics technologies.

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Authors
Rosenberger, F. A., Thielert, M., Strauss, M. T., Schweizer, L., Ammar, C., Mädler, S. C., Metousis, A., Skowronek, P., Wahle, M., Madden, K., Gote-Schniering, J., Semenova, A., Schiller, H. B., Rodriguez, E., Nordmann, T. M., Mund, A., & Mann, M.
Affiliations
  • Max Planck Institute of Biochemistry (DE)
  • University of Copenhagen (DK)
  • Helmholtz Munich (DE)
Corresponding author
Mann, Matthias
Venue
Nature Methods
Published
2023-10
Volume
20
Issue
10
Pages
1530-1536
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
OpenAlex
W4387266998
Cited by
176
References
36
Citations by year
2026: 49 · 2025: 62 · 2024: 48 · 2023: 17
FWCI
16.23
Type
journal article
Language
en
Open access
Locations
  • Nature Methods (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
Funders
  • Fund for Astrophysical Research
  • European Respiratory Society (847462)
  • Chan Zuckerberg Initiative (CZF2019-002448)
  • European Commission (H2020, 825694, 874839, 847462)
  • Boehringer Ingelheim Fonds
  • Max-Planck-Gesellschaft
  • Novo Nordisk (NNF14CC0001, NNF15CC0001)
  • Novo Nordisk Fonden (NNF 14CC0001, NNF15CC0001)
  • Horizon 2020 Framework Programme (874839, 825694, 847462)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
spatial proteomics, single-cell proteomics, hepatocytes, liver zonation, central vein, laser microdissection, high-content imaging, machine learning
MeSH terms
Animals, Mass Spectrometry, Proteome, Proteomics, Mice, Laser Capture Microdissection

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