Unbiased spatial proteomics with single-cell resolution in tissues
Open accessAbstract
Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.
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References 109 · Cited by 259
- Authors
- Mund, A., Brunner, A.-D., & Mann, M.
- Affiliations
- University of Copenhagen (DK)
- Boehringer Ingelheim (Germany) (DE)
- Corresponding author
- Mann, Matthias
- Venue
- Molecular Cell
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 82
- Issue
- 12
- Pages
- 2335-2349
- ISSN
- 1097-2765 (ISSN-L)
- OpenAlex
- W4283032464
- Semantic Scholar
- b359e661374bdabf0d8f01cf10019d51ed040c67
- Cited by
- 259
- References
- 109
- Citations by year
- 2026: 54 · 2025: 67 · 2024: 65 · 2023: 66 · 2022: 7
- FWCI
- 6.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 380 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Molecular Cell (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion)
- Funders
- Novo Nordisk Fonden (NNF14CC0001, NNF15CC0001)
- Chan Zuckerberg Initiative (CZF2019-002448)
- Max-Planck-Gesellschaft
- 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, single-cell transcriptomics, stochastic noise, multiplexed imaging, spatial transcriptomics, high-content imaging, precision medicine
- MeSH terms
- Artificial Intelligence, Mass Spectrometry, Proteome, Proteomics
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