Dataset Information

Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topology

ABSTRACT: The specific functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-linking assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome in a single experiment. Biochemical and imaging-based follow-up studies demonstrate that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, establishes a method for concomitant profiling of sub-organelle and membrane proteomes, and provides a resource for mitochondrial spatial biology

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Kerem Akkaya

LAB HEAD: Fan Liu

PROVIDER: PXD046382 | Pride | 2024-02-21

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	L1_20210428_CW_25_HEK_mito_HPH_A10.raw	Raw
	L1_20210428_CW_25_HEK_mito_HPH_A11.raw	Raw
	L1_20210428_CW_25_HEK_mito_HPH_A12.raw	Raw
	L1_20210428_CW_25_HEK_mito_HPH_A7.raw	Raw
	L1_20210428_CW_25_HEK_mito_HPH_A8.raw	Raw

Items per page:

1 - 5 of 48

Similar Datasets

Project description:Cellular functional pathways have evolved through selection based on fitness benefits conferred through protein intra- and inter-molecular interactions that comprise all protein conformational features and protein-protein interactions, collectively referred to as the interactome. While the interactome is regulated by proteome levels, it is also regulated independently by, post translational modification, co-factor, and ligand levels, as well as local protein environmental factors, such as osmolyte concentration, pH, ionic strength, temperature and others. In modern biomedical research, cultivatable cell lines have become an indispensable tool, with selection of optimal cell lines that exhibit specific functional profiles being critical for success in many cases. While it is clear that cell lines derived from different cell types have differential proteome levels, increased understanding of large-scale functional differences requires additional information beyond abundance level measurements, including how protein conformations and interactions are altered in certain cell types to shape functional landscapes. Here, we employed quantitative in vivo protein cross-linking coupled to mass spectrometry to probe large-scale protein conformational and interaction changes among three commonly employed human cell lines, HEK293, MCF-7, and HeLa cells. Isobaric quantitative Protein Interaction Reporter (iqPIR) technologies were used to obtain quantitative values of cross-linked peptides across three cell lines. These data illustrated highly reproducible (R2 values larger than 0.8 for all biological replicates) quantitative interactome levels across multiple biological replicates. We also measured protein abundance levels in these cells using data independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteomics information allowed visualization of cell type-specific interactome changes mediated by proteome level adaptations as well as independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the biggest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study systems-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight on cellular functional landscapes.

Dataset Information

Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topology

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets