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Mapping Glycan to Glycan Binding Protein (GBP) Interactions by Live Cell Proximity Tagging
The interactions between glycans and glycan-binding proteins (GBPs) consist of weak, non-covalent, and transient binding events, making them difficult to study in live cells, void of a static, isolated system. Furthermore, the glycans are often presented as protein glycoconjugates, yet there are lim...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274366/ https://www.ncbi.nlm.nih.gov/pubmed/33861898 http://dx.doi.org/10.1002/cpz1.104 |
Sumario: | The interactions between glycans and glycan-binding proteins (GBPs) consist of weak, non-covalent, and transient binding events, making them difficult to study in live cells, void of a static, isolated system. Furthermore, the glycans are often presented as protein glycoconjugates, yet there are limited efforts to identify these proteins. Proximity labeling permits the covalent tagging of the glycoprotein interactors for a query GBP in live cells, and coupled with high-resolution mass spectrometry (MS), it facilitates the determination of the proteins bearing the interacting glycans. In this method, fusion protein constructs of a GBP of interest with a peroxidase enzyme allows for the in situ spatiotemporal radical-mediated tagging of interacting glycoproteins in living cells that can be enriched for identification. Using this method, the capture and study of glycan-GBP interactions no longer relies on weak, transient interactions and results in robust capture and identification of the interactome of a GBP, while preserving the native cellular environment. This protocol focuses on the (1) expression and characterization of a recombinant fusion protein between a peroxidase enzyme and a GBP called galectin-3, (2) the corresponding in situ labeling and visualization of interactors, (3) and the proteomic workflow and analysis of the captured proteins for robust identification using MS. |
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