Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome
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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.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Nature Methods |
| Vol/bind | 20 |
| Udgave nummer | 10 |
| Sider (fra-til) | 1530-1536 |
| Antal sider | 7 |
| ISSN | 1548-7091 |
| DOI | |
| Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
We thank our colleagues at the Department of Proteomics and Signal Transduction at the Max Planck Institute of Biochemistry as well as our colleagues at the Center for Proteome Research in Copenhagen for their input and support. We are particularly grateful for input and help from I. Bludau, A. Brunner and L. Zeitler. We thank Peter H. and Single-Cell Technologies Ltd. for their technical support. F.A.R. is an EMBO postdoctoral fellow (ALTF 399-2021). S.C.M. is a PhD fellow of the Boehringer Ingelheim Fonds. J.G.-S. has received funding from the European Respiratory Society and the European Union’s H2020 research and innovation program under the Marie Sklodowska-Curie RESPIRE4 grant agreement no. 847462. This study has been supported by the Horizon-2020 under the MICROB-PREDICT program (M.M., no. 825694) and ISLET (M.M., no. 874839), by the Max Planck Society for Advancement of Science (M.M.), by the Chan Zuckerberg Initiative (M.M., CZF2019-002448) and by grants from the Novo Nordisk Foundation, Denmark (M.M., grant agreements NNF14CC0001 and NNF15CC0001). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Funding Information:
We thank our colleagues at the Department of Proteomics and Signal Transduction at the Max Planck Institute of Biochemistry as well as our colleagues at the Center for Proteome Research in Copenhagen for their input and support. We are particularly grateful for input and help from I. Bludau, A. Brunner and L. Zeitler. We thank Peter H. and Single-Cell Technologies Ltd. for their technical support. F.A.R. is an EMBO postdoctoral fellow (ALTF 399-2021). S.C.M. is a PhD fellow of the Boehringer Ingelheim Fonds. J.G.-S. has received funding from the European Respiratory Society and the European Union’s H2020 research and innovation program under the Marie Sklodowska-Curie RESPIRE4 grant agreement no. 847462. This study has been supported by the Horizon-2020 under the MICROB-PREDICT program (M.M., no. 825694) and ISLET (M.M., no. 874839), by the Max Planck Society for Advancement of Science (M.M.), by the Chan Zuckerberg Initiative (M.M., CZF2019-002448) and by grants from the Novo Nordisk Foundation, Denmark (M.M., grant agreements NNF14CC0001 and NNF15CC0001). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Publisher Copyright:
© 2023, The Author(s).
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