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

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 HP1 gamma. 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-HP1 gamma + BirA-HP1 gamma experiments. Skyline can also be applied for the analysis and identification of PPIs from shotgun proteomics data downloaded from publicly available datasets and repositories.

Automated summary

This paper discusses the use of Skyline software for the quantification of protein-protein interactions in cells by analyzing biotinylated form of the biotin acceptor peptide tag. Experimental results showed high levels of biotinylation in the presence of pluripotency transcription factors Sox2 and Oct4, and heterochromatin protein HP1 gamma. Skyline software can also be utilized for analyzing PPIs from shotgun proteomics data obtained from public datasets and repositories.