Profiling the E. coli membrane interactome captured in peptidisc libraries
Abstract
Protein-correlation-profiling (PCP), in combination with quantitative proteomics, has emerged as a high-throughput method for the rapid identification of dynamic protein complexes in native conditions. While PCP has been successfully applied to soluble proteomes, characterization of the membrane interactome has lagged, partly due to the necessary use of detergents to maintain protein solubility. Here, we apply the peptidisc, a 'one-size fits all' membrane mimetic, for the capture of the Escherichia coli cell envelope proteome and its high-resolution fractionation in the absence of detergent. Analysis of the SILAC-labeled peptidisc library via PCP allows generation of over 4900 possible binary interactions out of >700,000 random associations. Using well-characterized membrane protein systems such as the SecY translocon, the Bam complex and the MetNI transporter, we demonstrate that our dataset is a useful resource for identifying transient and surprisingly novel protein interactions, some of them with profound biological implications, and many of them largely undetected by standard detergent-based purification. The peptidisc workflow applied to the proteomic field is a promising novel approach to characterize membrane protein interactions under native expression conditions and without genetic manipulation.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
Canadian Institutes of Health Research
- Franck Van Hoa Duong
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Nir Ben-Tal, Tel Aviv University, Israel
Publication history
- Received: March 7, 2019
- Accepted: July 30, 2019
- Accepted Manuscript published: July 31, 2019 (version 1)
- Version of Record published: August 16, 2019 (version 2)
Copyright
© 2019, Carlson et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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