Literature DB >> 34885753

Application of Skyline for Analysis of Protein-Protein Interactions In Vivo.

Arman Kulyyassov1.   

Abstract

Quantitative and qualitative analyses of cell protein composition using liquid chromatography/tandem mass spectrometry are now standard techniques in biological and clinical research. However, the quantitative analysis of protein-protein interactions (PPIs) in cells is also important since these interactions are the bases of many processes, such as the cell cycle and signaling pathways. This paper describes the application of Skyline software for the identification and quantification of the biotinylated form of the biotin acceptor peptide (BAP) tag, which is a marker of in vivo PPIs. The tag was used in the Proximity Utilizing Biotinylation (PUB) method, which is based on the co-expression of BAP-X and BirA-Y in mammalian cells, where X or Y are interacting proteins of interest. A high level of biotinylation was detected in the model experiments where X and Y were pluripotency transcription factors Sox2 and Oct4, or heterochromatin protein HP1γ. MRM data processed by Skyline were normalized and recalculated. Ratios of biotinylation levels in experiment versus controls were 86 ± 6 (3 h biotinylation time) and 71 ± 5 (9 h biotinylation time) for BAP-Sox2 + BirA-Oct4 and 32 ± 3 (4 h biotinylation time) for BAP-HP1γ + BirA-HP1γ experiments. Skyline can also be applied for the analysis and identification of PPIs from shotgun proteomics data downloaded from publicly available datasets and repositories.

Entities:  

Keywords:  biotin acceptor peptide (BAP); biotin ligase BirA; liquid chromatography tandem mass spectrometry (LC-MS/MS); multiple reaction monitoring (MRM); protein–protein interactions (PPIs); proteomics; proximity utilizing biotinylation (PUB)

Mesh:

Substances:

Year:  2021        PMID: 34885753      PMCID: PMC8658920          DOI: 10.3390/molecules26237170

Source DB:  PubMed          Journal:  Molecules        ISSN: 1420-3049            Impact factor:   4.411


  44 in total

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Journal:  Mol Cell Proteomics       Date:  2018-02-27       Impact factor: 5.911

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Journal:  Mol Cell Proteomics       Date:  2014-01-17       Impact factor: 5.911

10.  Efficient proximity labeling in living cells and organisms with TurboID.

Authors:  Tess C Branon; Justin A Bosch; Ariana D Sanchez; Namrata D Udeshi; Tanya Svinkina; Steven A Carr; Jessica L Feldman; Norbert Perrimon; Alice Y Ting
Journal:  Nat Biotechnol       Date:  2018-08-20       Impact factor: 54.908

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  1 in total

1.  Generation of Peptides for Highly Efficient Proximity Utilizing Site-Specific Biotinylation in Cells.

Authors:  Arman Kulyyassov; Yerlan Ramankulov; Vasily Ogryzko
Journal:  Life (Basel)       Date:  2022-02-16
  1 in total

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