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Nat Protoc. 2016 Dec;11(12):2515-2528. doi: 10.1038/nprot.2016.140. Epub 2016 Nov 17.

Deep interactome profiling of membrane proteins by co-interacting protein identification technology.

Author information

1
Department of Chemical Physiology, The Scripps Research Institute, La Jolla, California, USA.
2
Department of Physics, Albert-Ludwigs-University Freiburg, Freiburg, Germany.

Abstract

Affinity purification coupled to mass spectrometry (AP-MS) is the method of choice for analyzing protein-protein interactions, but common protocols frequently recover only the most stable interactions and tend to result in low bait yield for membrane proteins. Here, we present a novel, deep interactome sequencing approach called CoPIT (co-interacting protein identification technology), which allows comprehensive identification and analysis of membrane protein interactomes and their dynamics. CoPIT integrates experimental and computational methods for a coimmunoprecipitation (Co-IP)-based workflow from sample preparation for mass spectrometric analysis to visualization of protein-protein interaction networks. The approach particularly improves the results for membrane protein interactomes, which have proven to be difficult to identify and analyze. CoPIT was used successfully to identify the interactome of the cystic fibrosis transmembrane conductance regulator (CFTR), demonstrating its validity and performance. The experimental step in this case achieved up to 100-fold-higher bait yield than previous methods by optimizing lysis, elution, sample clean-up and detection of interacting proteins by multidimensional protein identification technology (MudPIT). Here, we further provide evidence that CoPIT is applicable to other types of proteins as well, and that it can be successfully used as a general Co-IP method. The protocol describes all steps, ranging from considerations for experimental design, Co-IP, preparation of the sample for mass spectrometric analysis, and data analysis steps, to the final visualization of interaction networks. Although the experimental part can be performed in <3 d, data analysis may take up to a few weeks.

PMID:
27854364
PMCID:
PMC5444904
DOI:
10.1038/nprot.2016.140
[Indexed for MEDLINE]
Free PMC Article

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