In the endomembrane system, multivesicular bodies (MVBs) play a crucial role in sorting ubiquitinated membrane proteins into intraluminal vesicles for degradation upon fusion with vacuoles or lysosomes. This process involves regulations by multiprotein complexes, including endosomal sorting complex required for transport (ESCRT) I-III, and accessory proteins. Although many organellar proteomes have been identified in plant cells, the information of specific proteomes associated with regulators engaged in MVB biogenesis remains limited. Here, using the ESCRT component FREE1 as an example, we describe a method to identify neighboring proteins of endosomal regulators by using an approach of TurboID-based proximity labeling.

Sequestosome1 (SQSTM1) is an autophagy receptor that mediates degradation of intracellular cargo, including protein aggregates, through multiple protein interactions. These interactions form the SQSTM1 protein network, and these interactions are mediated by SQSTM1 functional interaction domains, which include LIR, PB1, UBA and KIR. Technological advances in cell biology continue to expand our knowledge of the SQSTM1 protein network and of the relationship of the actions of the SQSTM1 protein network in cellular physiology and disease states. Here we apply proximity profile labeling to investigate the SQSTM1 protein interaction network by fusing TurboID with the human protein SQSTM1 (TurboID::SQSTM1). This chimeric protein displayed well-established SQSTM1 features including production of SQSTM1 intracellular bodies, binding to known SQSTM1 interacting partners, and capture of novel SQSTM1 protein interactors. Strikingly, aggregated tau protein altered the protein interaction network of SQSTM1 to include many stress-associated proteins. We demonstrate the importance of the PB1 and/or UBA domains for binding network members, including the K18 domain of tau. Overall, our work reveals the dynamic landscape of the SQSTM1 protein network and offers a resource to study SQSTM1 function in cellular physiology and disease state.

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In recent years, proximity labeling has established itself as an unbiased and powerful approach to map the interactome of specific proteins. While physiological expression of labeling enzymes is beneficial for the mapping of interactors, generation of the desired cell lines remains time-consuming and challenging. Using our established pipeline for rapid generation of C- and N-terminal CRISPR-Cas9 knock-ins (KIs) based on antibiotic selection, we were able to compare the performance of commonly used labeling enzymes when endogenously expressed. Endogenous tagging of the µ subunit of the AP-1 complex with TurboID allowed identification of known interactors and cargo proteins that simple overexpression of a labeling enzyme fusion protein could not reveal. We used the KI-strategy to compare the interactome of the different adaptor protein (AP) complexes and clathrin and were able to assemble lists of potential interactors and cargo proteins that are specific for each sorting pathway. Our approach greatly simplifies the execution of proximity labeling experiments for proteins in their native cellular environment and allows going from CRISPR transfection to mass spectrometry analysis and interactome data in just over a month.

Virus receptors determine the tissue tropism of viruses and have a certain relationship with the clinical outcomes caused by viral infection, which is of great importance for the identification of virus receptors to understand the infection mechanism of viruses and to develop entry inhibitor. Proximity labeling (PL) is a new technique for studying protein-protein interactions, but it has not yet been applied to the identification of virus receptors or co-receptors. Here, we attempt to identify co-receptor of SARS-CoV-2 by employing TurboID-catalyzed PL. The membrane protein angiotensin-converting enzyme 2 (ACE2) was employed as a bait and conjugated to TurboID, and a A549 cell line with stable expression of ACE2-TurboID was constructed. SARS-CoV-2 pseudovirus were incubated with ACE2-TurboID stably expressed cell lines in the presence of biotin and ATP, which could initiate the catalytic activity of TurboID and tag adjacent endogenous proteins with biotin. Subsequently, the biotinylated proteins were harvested and identified by mass spectrometry. We identified a membrane protein, AXL, that has been functionally shown to mediate SARS-CoV-2 entry into host cells. Our data suggest that PL could be used to identify co-receptors for virus entry.

Protein-protein interactions play an important biological role in every aspect of cellular homeostasis and functioning. Proximity labeling mass spectrometry-based proteomics overcomes challenges typically associated with other methods and has quickly become the current state of the art in the field. Nevertheless, tight control of proximity-labeling enzymatic activity and expression levels is crucial to accurately identify protein interactors. Here, we leverage a T2A self-cleaving peptide and a non-cleaving mutant to accommodate the protein of interest in the experimental and control TurboID setup. To allow easy and streamlined plasmid assembly, we built a Golden Gate modular cloning system to generate plasmids for transient expression and stable integration. To highlight our T2A Split/link design, we applied it to identify protein interactions of the glucocorticoid receptor and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid and non-structural protein 7 (NSP7) proteins by TurboID proximity labeling. Our results demonstrate that our T2A split/link provides an opportune control that builds upon previously established control requirements in the field.

Seipin, a crucial protein for cellular lipid droplet (LD) assembly, oligomerizes at the interface between the endoplasmic reticulum and LDs to facilitate neutral lipid packaging. Using proximity labeling, we identified four proteins-Ldo45, Ldo16, Tgl4, and Pln1-that are recruited to the vicinity of yeast seipin, the Sei1-Ldb16 complex, exclusively when seipin function is intact, hence termed seipin accessory factors. Localization studies identified Tgl4 at the endoplasmic reticulum-LD contact site, in contrast to Ldo45, Ldo16, and Pln1 at the LD surface. Cells with compromised seipin function resulted in uneven distribution of these proteins with aberrant LDs, supporting a central role of seipin in orchestrating their association with the LD. Overexpression of any seipin accessory factor causes LD aggregation and affects a subset of LD protein distribution, highlighting the importance of their stoichiometry. Although single factor mutations show minor LD morphology changes, the combined mutations have additive effects. Lastly, we present evidence that seipin accessory factors assemble and interact with seipin in the absence of neutral lipids and undergo dynamical rearrangements during LD formation induction, with Ldo45 acting as a central hub recruiting other factors to interact with the seipin complex.

G-protein-coupled receptors (GPCRs) are hepta-helical transmembrane proteins that mediate various intracellular signaling events in response to their specific ligands including many lipid mediators. Although analyses of GPCR molecular interactions are pivotal to understanding diverse intracellular signaling events, affinity purification of interacting proteins by a conventional co-immunoprecipitation method is challenging due to the hydrophobic nature of GPCRs and their dynamic molecular interactions. Proximity labeling catalyzed by a TurboID system is a powerful technique for defining the molecular interactions of target proteins in living cells. TurboID and miniTurbo (a modified version of TurboID) are engineered biotin ligases that biotinylate neighboring proteins in a promiscuous manner. When fused with a target protein and expressed in living cells, TurboID or miniTurbo mediates the biotin labeling of the proteins with close proximity to the target protein, allowing efficient purification of the biotinylated proteins followed by a shot-gun proteomic analysis. In this chapter, we describe a step-by-step protocol for the labeling of GPCR neighboring proteins by TurboID or miniTurbo, purification of the biotin-labeled proteins, and subsequent sample preparation for proteomic analysis. We utilized S1PR1 as a model GPCR, a receptor for a bioactive lipid molecule sphingosine 1-phosphate (S1P) that plays various roles in physiological and pathological conditions. This analysis pipeline enables the mapping of interacting proteins of lipid GPCRs in living cells.

Protein-protein interaction studies using proximity labeling techniques, such as biotin ligase-based BioID, have become integral in understanding cellular processes. Most studies utilize conventional 2D cell culture systems, potentially missing important differences in protein behavior found in 3D tissues. In this study, we investigated the protein-protein interactions of a protein, Bcl-2 Agonist of cell death (BAD), and compared conventional 2D culture conditions to a 3D system, wherein cells were embedded within a 3D extracellular matrix (ECM) mimic. Using BAD fused to the engineered biotin ligase miniTurbo (BirA*), we identified both overlapping and distinct BAD interactomes under 2D and 3D conditions. The known BAD binding proteins 14-3-3 isoforms and Bcl-XL interacted with BAD in both 2D and 3D. Of the 131 BAD-interactors identified, 56% were specific to 2D, 14% were specific to 3D, and 30% were common to both conditions. Interaction network analysis demonstrated differential associations between 2D and 3D interactomes, emphasizing the impact of the culture conditions on protein interactions. The 2D-3D overlap interactome encapsulated the apoptotic program, which is a well-known role of BAD. The 3D unique pathways were enriched in ECM signaling, suggestive of hitherto unknown functions for BAD. Thus, exploring protein-protein interactions in 3D provides novel clues into cell behavior. This exciting approach has the potential to bridge the knowledge gap between tractable 2D cell culture and organoid-like 3D systems.

Single-cell-type proteomics is an emerging field of research that combines cell-type specificity with the comprehensive proteome coverage offered by bulk proteomics. However, the extraction of single-cell-type proteomes remains a challenge, particularly for hard-to-isolate cells like neurons. In this chapter, we present an innovative technique for profiling single-cell-type proteomes using adeno-associated virus (AAV)-mediated proximity labeling (PL) and tandem-mass-tag (TMT) mass spectrometry. This technique eliminates the need for cell isolation and offers a streamlined workflow, including AAV delivery to express TurboID (an engineered biotin ligase) controlled by cell-type-specific promoters, biotinylated protein purification, on-bead digestion, TMT labeling, and liquid chromatography-mass spectrometry (LC-MS). We examined this method by analyzing distinct brain cell types in mice. Initially, recombinant AAVs were used to concurrently express TurboID and mCherry proteins driven by neuron- or astrocyte-specific promoters, which was validated through co-immunostaining with cellular markers. With biotin purification and TMT analysis, we successfully identified around 10,000 unique proteins from a few micrograms of protein samples with high reproducibility. Our statistical analyses revealed that these proteomes encompass cell-type-specific cellular pathways. By utilizing this technique, researchers can explore the proteomic landscape of specific cell types, paving the way for new insights into cellular processes, deciphering disease mechanisms, and identifying therapeutic targets in neuroscience and beyond.