MassIVE MSV000093995

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All-at-once spatial proteome profiling of complex tissue context with single-cell-type resolution by proximity proteomics

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Description

Spatial proteomics enables in-depth mapping of cellular components and tissue architectures, mostly achieved by laser microdissection-mass spectrometry (LMD-MS) and antibody-based imaging. However, the trade-offs among sampling resolution, throughput, and proteome coverage still limit the applicability of these strategies, especially toward deep proteome profiling with high spatial resolution. Here, we propose PSPro (Proximity labeling for Spatial Proteomics) by leveraging precise antibody-targeted biotinylation at three-dimension scale and efficient affinity purification for MS-based cell-type-specific proteome profiling from single tissue slice. With fine-tuned labeling parameters, PSPro achieves all-at-once cell-type proteome capture with sub-micrometer resolution and shows comparable performance to flow cytometry- and LMD-based proteomic workflows. We apply PSPro to fixed tumor and spleen slices, enriching thousands of proteins containing known markers from ten cell types. For tissue microenvironments with high heterogeneity, we further incorporate region-resolved LMD into PSPro to facilitate direct comparison of cell subpopulations from the same tissue slice, revealing spatial proteome heterogeneity of cancer cells and immune cells in pancreatic tumor. Collectively, PSPro converts traditional “antibody-epitope” paradigm to “antibody-cell type proteome” for spatial biology in a user-friendly manner. [doi:10.25345/C5X921W0T] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: spatial proteomics, proximity labeling

Contact

Principal Investigators:
(in alphabetical order) 		Ruijun Tian, SUSTech, China
Submitting User: MaoYiheng
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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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