Dataset Information

Deep single-cell type proteome profiling of mouse brain by nonsurgical AAV-mediated proximity labeling

ABSTRACT: Proteome profiling is a powerful tool in biological and biomedical studies, starting with samples at bulk, single cell, or single cell type levels. Reliable methods for extracting specific cell type proteome are in need, especially for the cells (e.g., neurons) that cannot be readily isolated. Here, we present an innovative proximity labeling (PL) strategy for single cell type proteomics of mouse brain, in which TurboID (an engineered biotin ligase) is used to label almost all proteins in a specific cell type. This strategy bypasses the requirement of cell isolation and includes five major steps: (i) constructing recombinant adeno-associated viruses (AAV) to express TurboID driven by cell type-specific promoters, (ii) delivering the AAV to mouse brains by direct intravenous injection, (iii) enhancing PL labeling by biotin administration, (iv) purifying biotinylated proteins followed by on-bead protein digestion, and (v) quantitative tandem-mass-tag (TMT). We first confirmed that TurboID can label a wide range of cellular proteins in human HEK293 cells and optimized the single cell type proteomics pipeline. To analyze specific brain cell types, we generated recombinant AAVs to express TurboID-mCherry fusion proteins, driven by neuron- or astrocyte-specific promoters, and validated the expected cell expression by co-immunostaining of mCherry and cellular markers. Subsequent biotin purification and TMT analysis identified ~10,000 unique proteins from a few micrograms of protein samples with excellent reproducibility. Comparative and statistical analysis indicated these PL proteomes contain cell type specific cellular pathways. Although proximity labeling was originally developed for studying protein-protein interactions and subcellular proteomes, we extend it to efficiently tag the entire proteomes of specific cell types in the mouse brain using TurboID biotin ligase. This simple, effective in vivo approach should be broadly applicable to single cell type proteomics.

INSTRUMENT(S): Thermo Q-Exactive HF (QE) Quadrupole-Obitrap mass spectrometer

ORGANISM(S): Mus <mouse, Genus> (ncbitaxon:10088) Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Junmin Peng

PROVIDER: MSV000088866 | MassIVE | Fri Feb 18 07:35:00 GMT 2022

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Proteome profiling is a powerful tool in biological and biomedical studies, starting with samples at bulk, single cell, or single cell type levels. Reliable methods for extracting specific cell type proteome are in need, especially for the cells (e.g., neurons) that cannot be readily isolated. Here, we present an innovative proximity labeling (PL) strategy for single cell type proteomics of mouse brain, in which TurboID (an engineered biotin ligase) is used to label almost all proteins in a specific cell type. This strategy bypasses the requirement of cell isolation and includes five major steps: (i) constructing recombinant adeno-associated viruses (AAV) to express TurboID driven by cell type-specific promoters, (ii) delivering the AAV to mouse brains by direct intravenous injection, (iii) enhancing PL labeling by biotin administration, (iv) purifying biotinylated proteins followed by on-bead protein digestion, and (v) quantitative tandem-mass-tag (TMT). We first confirmed that TurboID can label a wide range of cellular proteins in human HEK293 cells and optimized the single cell type proteomics pipeline. To analyze specific brain cell types, we generated recombinant AAVs to express TurboID-mCherry fusion proteins, driven by neuron- or astrocyte-specific promoters, and validated the expected cell expression by co-immunostaining of mCherry and cellular markers. Subsequent biotin purification and TMT analysis identified ~10,000 unique proteins from a few micrograms of protein samples with excellent reproducibility. Comparative and statistical analysis indicated these PL proteomes contain cell type specific cellular pathways. Although proximity labeling was originally developed for studying protein-protein interactions and subcellular proteomes, we extend it to efficiently tag the entire proteomes of specific cell types in the mouse brain using TurboID biotin ligase. This simple, effective in vivo approach should be broadly applicable to single cell type proteomics.

Project description:Classical methods of investigating protein-protein interactions (PPIs) are generally performed in non-living systems, yet in recent years new technologies utilizing proximity labeling (PL) have given researchers the tools to explore proximal PPIs in living systems. PL has distinct advantages over traditional protein interactome studies, such as the ability to identify weak and transient interactions in vitro and in vivo. Most PL studies are performed on targets within or on the cell membrane. We have adapted the original PL method to investigate PPIs within the extracellular compartment, using both BioID2 and TurboID, that we term extracellular PL (ePL). To demonstrate the utility of this modified technique, we investigate the interactome of the widely expressed matrisome protein Tissue inhibitors of metalloproteinases 2 (TIMP2). Tissue inhibitors of metalloproteinases (TIMPs) are a family of multi-functional proteins that were initially defined by their ability to inhibit the enzymatic activity of metalloproteinases (MPs), the major mediators of extracellular matrix (ECM) breakdown and turnover. TIMP2 exhibits a broad expression profile and is often abundant in both normal and diseased tissues. Understanding the functional transformation of matrisome regulators, like TIMP2, during the evolution of tissue microenvironments associated with disease progression is essential for the development of ECM targeted therapeutics. Using carboxyl- and amino-terminal fusion proteins of TIMP2 with BioID2 and TurboID, we describe the TIMP2 proximal interactome. We also illustrate how the TIMP2 interactome changes in the presence of different stimuli, in different cell types, in unique culture conditions (2D vs 3D), and with different reaction kinetics (BioID2 vs. TurboID); demonstrating the power of this technique versus classical PPI methods. We propose that the screening of matrisome targets in disease models using ePL will reveal new therapeutic targets for further comprehensive studies.

Dataset Information

Deep single-cell type proteome profiling of mouse brain by nonsurgical AAV-mediated proximity labeling

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets