Protein-protein interactions mediate essential cellular processes, however the detection of native interactions is challenging since they are often low affinity and context dependent. Here, we develop a chemical proteomics approach in vivo CLASPI [iCLASPI] (in vivo crosslinking-assisted and stable isotope labeling by amino acids in cell culture [SILAC]-based protein identification) relying upon photo-crosslinking, amber suppression, and SILAC-based quantitative proteomics to profile context-dependent protein-protein interactions in living cells. First, we use iCLASPI to profile in vivo binding partners of the N-terminal tails of soluble histone H3 or H4. We identify known histone chaperones and modifying proteins, thereby validating our approach, and find an interaction between soluble histone H3 and UBR7, an E3 ubiquitin ligase, mediated by UBR7's PHD domain. Furthermore, we apply iCLASPI to profile the context-dependent protein-protein interactions of chromatin-associated histone H3 at different cell-cycle stages, and identify ANP32A as a mitosis-specific interactor. Our results demonstrate that the iCLASPI approach can provide a general strategy for identifying native, context-dependent direct protein-protein interactions using photo-crosslinking and quantitative proteomics.
Pubmed ID: 29104064 RIS Download
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A quantitative proteomics software package for analyzing large-scale mass-spectrometric data sets. It is a set of algorithms that include peak detection and scoring of peptides, mass calibration, database searches for protein identification, protein quantification, and provides summary statistics.
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