Background

In the post-genomic era, deciphering the intricate and dynamic network of protein–protein interactions within cells has become pivotal for unraveling the mysteries of life. Proximity Labeling As an emerging approach for capturing protein–protein interactions, technology is rapidly becoming a “powerful tool” in life sciences research due to its high spatiotemporal resolution and suitability for use in living cells and intact organisms.

Nearby Marker Flowchart ^[1]

This article focuses on a comparative analysis of the strengths and weaknesses of different construction strategies for proximity labeling technologies, helping you to precisely target your research design.

I. Introduction to Proximity Labeling Technology

Proximity labeling is an engineered-enzyme–based method for probing protein–protein interactions. The core principle involves fusing a catalytically active labeling enzyme—such as TurboID, APEX2, miniTurbo, or AirID—to the protein of interest, enabling it under specific conditions to catalyze the covalent biotinylation of nearby proteins within a 5–10 nm range. This biotinylated proximal proteome can then be enriched using streptavidin and subjected to mass spectrometry-based identification, thereby revealing the microenvironment of the target protein.

Additional reading: Literature Review | AirID: A New Chapter in Protein Interaction Research [Save]

II. Research Value and Typical Applications of Proximity Markers

1) Constructing protein interaction maps (Interactome Mapping): revealing the proximity networks of specific proteins or complexes, thereby addressing the limitations of traditional co-immunoprecipitation assays.

2) Subcellular localization and microenvironment analysis: localize labeled enzymes to specific organelles (such as mitochondria and lysosomes) or membrane structures, and analyze the region-specific protein composition.

3) Protein transport and dynamic signaling tracking: Investigating changes in the composition of protein complexes in response to stimulation or pharmacological intervention.

4) In vivo studies of protein–protein interactions: Leveraging the low toxicity of TurboID and miniTurbo, tissue-specific interactions can be investigated in mice or zebrafish.

III. Selection of Cell Line Construction Strategies: In Situ Knock-in vs. Overexpression Fusion

The construction of proximity labeling systems in cell lines is mainly divided into two categories:

3.1 Overexpression (OE)

3.1.1 Principle

The fusion protein (e.g., TurboID–target protein) is introduced into cells via an exogenous expression system (e.g., plasmids, electroporation, viruses, etc.), resulting in its high-level expression; typically, this occurs through random integration.

3.1.2 Construction Process

1) Clone the target protein and fuse it with a proximity-labeling enzyme (e.g., TurboID or APEX2) to construct an expression vector.

2) Introduce into cells using plasmids, lentiviruses, adeno-associated viruses (AAVs), and other methods.

3) After confirmation of expression, add the substrate (e.g., biotin or biotin-phenol) to perform the labeling experiment.

3.2 Endogenous Knock-in

3.2.1 Principle

Using CRISPR-Cas9 and other approaches, genes encoding proximity-labeling enzymes such as TurboID and APEX are genetically fused to endogenous gene loci (at the N- or C-terminus of the target gene) to achieve endogenous expression–mediated proximity labeling.

3.2.2 Construction Process

1) Design the sgRNA to target the region immediately upstream of the target gene’s stop codon, i.e., an insertion at the C-terminus (or an insertion at the N-terminus downstream of the start site).

2) Prepare donor DNA containing tags such as TurboID and homologous arms. 3) Electroporate or transduce cells with the donor DNA, then screen for successfully knocked-in monoclonal cell lines. 4) Verify the expression of the fusion protein and its functional integrity.

Comparison of Proximity Marker Construction Methods

 

IV. Reference Cases

4.1 Protein Interaction Screening (Overexpression)

Researchers, by combining TurboID with ZNF410 Overexpression fusion ^[2] , biotinylation of ZNF410-associated proteins was achieved, confirming that the chromatin-remodeling complex SWI/SNF is selectively recruited by the N-terminal domain of ZNF410. Through their synergistic action, they displace nucleosomes, thereby ensuring the efficient binding of ZNF410 to HCTs in enhancer regions and maintaining an open chromatin state at CHD4-enhancers.

4.2 Investigation of Disease Mechanisms (Overexpression)

Researchers have discovered a novel mechanism that regulates tau pathology aggregation. ^[3] : TRIAD3A through nesting Phase separation Promote tau amyloidization. The experiment was conducted using TurboID. Overexpression fusion TRIAD3A labels proximal proteins in living cells and identifies multiple proteins associated with neurodegenerative diseases, including tau. This study not only underscores the critical role of hierarchical organization in phase-separated structures in pathological protein aggregation but also offers new insights into the interplay among the ubiquitin system, phase separation, and autophagic clearance, thereby identifying potential therapeutic targets for interventions in Alzheimer’s disease and other disorders.

4.3 Construction of Interaction Maps (Overexpression & In Situ Knock-in)

Researchers comprehensively compared the performance differences between TurboID in situ knock-in (KI) and overexpression (OE) in proximity labeling experiments. , special attention Signal-to-noise ratio, the number of interacting proteins, and specificity Waiting indicators ^[4] 。

1) A comparison of biotin labeling efficiency revealed that the OE sample exhibited a very strong biotin signal, but also substantial background (non-specific labeling); in contrast, the KI sample showed a clear biotin signal with minimal background, and the signal distribution was more localized to the target region.

2) Analysis of the interacting proteins identified by the two methods revealed that the KI group exhibited a series of highly significant, true interactors with a low background of non-specific proteins, whereas the OE group, although detecting a greater number of proteins, suffered from a high background that obscured the genuine interactions. 3) Functional enrichment analysis of the interactors identified in both groups demonstrated that the biological processes enriched in the KI group were highly consistent with the functions of the target protein (e.g., nuclear processes, chromatin regulation), while the OE group showed a large number of unrelated pathways (e.g., extracellular matrix proteins).

4) Finally, the overall quality of the MS data was evaluated, and it was found that the KI method exhibits higher sensitivity.

In summary, the researchers believe that Endogenously expressed TurboID knock-in mice can generate more specific, accurate, and physiologically relevant protein interaction maps, making them a superior strategy compared with conventional overexpression approaches.

In summary, we have recommended different strategies for various application scenarios for your reference:

Liman offers end-to-end services for proximity labeling, including overexpression and in situ labeling strategies, Strep-tag affinity purification, and mass spectrometry-based detection. Please contact us for more information!

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Liman’s products and services related to “proximal protein labeling”:

1.  Construction of Stable Cell Lines with In Situ Gene Insertion/Overexpression ： In situ insertion of tags such as birID and TurboID at the N- or C-terminus of a gene enables proximity labeling-based detection, allowing the identification of protein–protein interactions, including weak and transient interactions. In situ insertion of tags like Strep-tag facilitates AP–MS analysis, revealing strong protein–protein interactions even at background levels. Random or safe-harbor site-specific insertion of “tag–target protein” constructs can generate overexpression cell lines for PL studies.

2. Leman Strept II Purification Packing Material : Enables ultra-high-affinity enrichment of Strep-tagged proteins and biotin-labeled proteins (e.g., those obtained via proximity labeling), with an affinity 100-fold higher than that of antibody-based enrichment;

3. AP-MS/IP-MS analysis : Perform mass spectrometry on cell samples tagged with proximity labels or affinity tags (Strep-tags) to identify interacting proteins;

4. Arrayed library screening for human/mouse gene knockout arrays : Designed for 19+ metabolic pathways (including a KO array library of over 300 E3 ubiquitin ligases and a KO array library of over 1,000 ubiquitin-related enzymes), offering higher precision, simplified data interpretation, strong experimental reproducibility, and broader research applicability.

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V. References

[1] Yang X, et al. Proximity labeling: an emerging tool for probing in planta molecular interactions. Plant Commun. 2020 Dec 15;2(2):100137.

[2] Xu S, et al. SWI/SNF complex-mediated ZNF410 cooperative binding maintains chromatin accessibility and enhancer activity. Cell Rep. 2025 Mar 28;44(4):115476. [3] Zhou J, et al. The autophagy adaptor TRIAD3A promotes tau fibrillation by nested phase separation. Nat Cell Biol. 2024 Aug;26(8):1274–1286. [4] Stockhammer A, et al. When less is more – a fast TurboID knock-in approach for high-sensitivity endogenous interactome mapping. J Cell Sci. 2024 Aug 15;137(16):jcs261952.