A Well-Controlled BioID Design for Endogenous Bait Proteins

Defining the interactomes of proteins involved in cytoskeletal dynamics using high-throughput proximity-dependent biotinylation in cellulo

Proximity-dependent biotinylation (BioID) screens are excellent tools to capture in cellulo interactomes for a large variety of baits, including transient and weak affinity interactions, as well as localization-specific proximity components, which are much harder to detect with conventional approaches. Here, we describe the major starting steps and a detailed protocol on how to perform BioID in mammalian cells. We also describe the mass spectrometry procedure and the bioinformatics pipeline for the data analysis.

For complete details on the use and execution of this profile, please refer to Bagci et al. (2020).

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Exploring the proximity interactome of proteins in cellulo in their native environment

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This BioID protocol is well-suited to determine the interactome of small GTPases

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Detailed steps of sample injection into mass spectrometer

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In-depth description of the bio-informatics analyses of BioID MS data

Orthogonal proteomics methods to unravel the HOTAIR interactome

Accumulating evidence highlights the role of long non-coding RNAs (lncRNAs) in cellular homeostasis, and their dysregulation in disease settings. Most lncRNAs function by interacting with proteins or protein complexes. While several orthogonal methods have been developed to identify these proteins, each method has its inherent strengths and limitations. Here, we combine two RNA-centric methods ChIRP-MS and RNA-BioID to obtain a comprehensive list of proteins that interact with the well-known lncRNA HOTAIR. Overexpression of HOTAIR has been associated with a metastasis-promoting phenotype in various cancers. Although HOTAIR is known to bind with PRC2 and LSD1 protein complexes, only very limited unbiased comprehensive approaches to map its interactome have been performed. Both ChIRP-MS and RNA-BioID data sets show an association of HOTAIR with mitoribosomes, suggesting that HOTAIR has functions independent of its (post-)transcriptional mode-of-action.

Applications of CRISPR-Cas Technologies to Proteomics

CRISPR-Cas-based genome editing is a revolutionary approach that has provided an unprecedented investigational power for the life sciences. Rapid and efficient, CRISPR-Cas technologies facilitate the generation of complex biological models and at the same time provide the necessary methods required to study these models in depth. The field of proteomics has already significantly benefited from leveraging the power of CRISPR-Cas technologies, however, many potential applications of these technologies in the context of proteomics remain unexplored. In this review, we intend to provide an introduction to the CRISPR-Cas technologies and demonstrate how they can be applied to solving proteome-centric questions. To achieve this goal, we begin with the description of the modern suite of CRISPR-Cas-based tools, focusing on the more mature CRISPR-Cas9 system. In the second part of this review, we highlight both established and potential applications of the CRISPR-Cas technologies to proteomics.

Protein Interaction Network Biology in Neuroscience

Mapping the intricate networks of cellular proteins in the human brain has the potential to address unsolved questions in molecular neuroscience, including the molecular basis of cognition, synaptic plasticity, long-term potentiation, learning, and memory. Perturbations to the protein-protein interaction networks (PPIN) present in neurons, glia, and other cell-types have been linked to multifactorial neurological disorders. Yet while knowledge of brain PPINs is steadily improving, the complexity and dynamic nature of the heterogeneous central nervous system in normal and disease contexts poses a formidable experimental challenge. In this review, the recent applications of functional proteomics and systems biology approaches to study PPINs central to normal neuronal function, during neurodevelopment, and in neurodegenerative disorders are summarized. How systematic PPIN analysis offers a unique mechanistic framework to explore intra- and inter-cellular functional modules governing neuronal activity and brain function is also discussed. Finally, future technological advancements needed to address outstanding questions facing neuroscience are outlined.

Keeping in Touch with Type-III Secretion System Effectors: Mass Spectrometry-Based Proteomics to Study Effector-Host Protein-Protein Interactions

Manipulation of host cellular processes by translocated bacterial effectors is key to the success of bacterial pathogens and some symbionts. Therefore, a comprehensive understanding of effectors is of critical importance to understand infection biology. It has become increasingly clear that the identification of host protein targets contributes invaluable knowledge to the characterization of effector function during pathogenesis. Recent advances in mapping protein-protein interaction networks by means of mass spectrometry-based interactomics have enabled the identification of host targets at large-scale. In this review, we highlight mass spectrometry-driven proteomics strategies and recent advances to elucidate type-III secretion system effector-host protein-protein interactions. Furthermore, we highlight approaches for defining spatial and temporal effector-host interactions, and discuss possible avenues for studying natively delivered effectors in the context of infection. Overall, the knowledge gained when unravelling effector complexation with host factors will provide novel opportunities to control infectious disease outcomes.

Proximity-dependent labeling methods for proteomic profiling in living cells: An update

Characterizing the proteome composition of organelles and subcellular regions of living cells can facilitate the understanding of cellular organization as well as protein interactome networks. Proximity labeling-based methods coupled with mass spectrometry (MS) offer a high-throughput approach for systematic analysis of spatially restricted proteomes. Proximity labeling utilizes enzymes that generate reactive radicals to covalently tag neighboring proteins. The tagged endogenous proteins can then be isolated for further analysis by MS. To analyze protein-protein interactions or identify components that localize to discrete subcellular compartments, spatial expression is achieved by fusing the enzyme to specific proteins or signal peptides that target to particular subcellular regions. Although these technologies have only been introduced recently, they have already provided deep insights into a wide range of biological processes. Here, we provide an updated description and comparison of proximity labeling methods, as well as their applications and improvements. As each method has its own unique features, the goal of this review is to describe how different proximity labeling methods can be used to answer different biological questions. This article is categorized under: Technologies > Analysis of Proteins.

Nb-induced stabilisation of p53 in HPV-infected cells

Cervical cancer is caused by a persistent infection of the mucosal epithelia with high-risk human papilloma viruses (HPVs). The viral oncoprotein E6 is responsible for the inactivation of the tumour suppressor p53 and thus plays a crucial role in HPV-induced tumorigenesis. The viral E6 protein forms a trimeric complex with the endogenous E3 ubiquitine ligase E6AP and the DNA-binding domain (DBD) of p53, which results in the polyubiquitination and proteasomal degradation of p53. We have developed nanobodies (Nbs) against the DBD of p53, which substantially stabilise p53 in HeLa cells. The observed effect is specific for HPV-infected cells, since similar effects were not seen for U2OS cells. Despite the fact that the stabilised p53 was strongly nuclear enriched, its tumour suppressive functions were hampered. We argue that the absence of a tumour suppressive effect is caused by inhibition of p53 transactivation in both HPV-infected and HPV-negative cells. The inactivation of the transcriptional activity of p53 was associated with an increased cellular proliferation and viability of HeLa cells. In conclusion, we demonstrate that p53 DBD Nbs positively affect protein stability whilst adversely affecting protein function, attesting to their ability to modulate protein properties in a very subtle manner.