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Overcoming preservation challenges to enable single-cell proteomics of fixed cell and tissue samples with retained proteome integrity

ABSTRACT: Recent advances in single-cell proteomics (SCP) now enable the unbiased quantification of the proteome to a depth of several thousand proteins across hundreds of cells. Yet the broader adoption beyond specialised groups remains limited due to the need for specific equipment and expertise. A major challenge in making these analyses more broadly available is sample preservation for transporting biological material to SCP-capable facilities. To address this issue and provide practical solutions, we first evaluated various cell preservation methods from monolayer culture samples, then tested our optimised methodology on both cultured cells and, for the first time, preserved animal tissue from an in vivo mouse model. Our findings highlight the feasibility of SCP analyses in preserved tissues, significantly expanding its current applicability. By optimising upstream processing, our approach enables robust single-cell proteome analysis of both cells and tissues, making SCP more accessible to the wider scientific community. Ultimately, this advancement expands the potential applications of SCP, particularly in disciplines where analysing rare or heterogeneous populations is beneficial.

INSTRUMENT(S): timsTOF SCP

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

TISSUE(S): Epithelial Cell, Cell Culture, Pancreas

DISEASE(S): Cancer

SUBMITTER: Agata Makar

LAB HEAD: Alex von Kriegsheim

PROVIDER: PXD061710 | Pride | 2025-05-23

REPOSITORIES: Pride

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			Action	DRS
	20230613_GSTP1KO_Figure1.zip	Other
	20230613_GSTP1KO_Figure1_search_engine_results.tsv	Tabular
	20230613_GSTP1KO_Figure1entrapment001.sne	Other
	20230613_GSTP1KO_Figure1entrapment015.sne	Other
	20230613_GSTP1KO_Figure1entrapmentDefault.sne	Other

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Project description:Single-cell proteomics (SCP) has advanced significantly, yet it remains largely unidimensional, focusing primarily on protein abundances. This limitation hinders our understanding of the dynamic processes occurring within individual cells, particularly protein turnover, which is crucial for cellular function and regulation. In this study, we employed a pulsed stable isotope labeling by amino acids in cell culture (SILAC) approach to simultaneously evaluate protein abundance and turnover in single cells (SC-pSILAC). Using state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ~4000 proteins in single HeLa cells recapitulating known biology. We investigated drug effects using protein synthesis and degradation inhibitors on global and specific protein turnover in single cells and performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSC) encompassing six sampling times over two months and analyzed >1000 cells. Abundance measurements highlighted cell-specific markers of stem cells and various organ-specific cell types. Protein turnover dynamics highlighted differentiation-specific co-regulation of core members of protein complexes with core histone turnover discriminating dividing and non-dividing cells with potential in stem cell and cancer research. Lastly, correlating the abundance of individual proteins from cells displaying a wide range of diameters show that histones and some proteins involved in the cell cycle do not scale with cell size confirming previous observations in yeast. Our study represents the most comprehensive SCP analysis to date, offering new insights into cellular diversity and pioneering functional post-translational measurements beyond protein abundance. This method not only distinguishes SCP from other single-cell omics approaches and enhances its scientific relevance in biological research in a multidimensional manner but also showcase the discovery potential of SCP in fundamental biology.

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Overcoming preservation challenges to enable single-cell proteomics of fixed cell and tissue samples with retained proteome integrity

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