Identifying key membrane protein lipid interactions using mass spectrometry

Journal article

With the recent success in determining membrane protein structures, further detailed understanding of the identity and function of the bound lipidome is essential. Using an approach that combines high-energy native mass spectrometry (HE-nMS) and solution-phase lipid profiling, this protocol can be used to determine the identity of the endogenous lipids that directly interact with a protein. Furthermore, this method can identify systems in which such lipid binding has a major role in regulating the oligomeric assembly of membrane proteins. The protocol begins with recording of the native mass spectrum of the protein of interest, under successive delipidation conditions, to determine whether delipidation leads to disruption of the oligomeric state. Subsequently, we propose using a bipronged strategy: first, an HE-nMS platform is used that allows dissociation of the detergent micelle at the front end of the instrument. This allows for isolation of the protein-lipid complex at the quadrupole and successive fragmentation at the collision cell, which leads to identification of the bound lipid masses. Next, simultaneous coupling of this with in-solution LC-MS/MS-based identification of extracted lipids reveals the complete identity of the interacting lipidome that copurifies with the proteins. Assimilation of the results of these two sets of experiments divulges the complete identity of the set of lipids that directly interact with the membrane protein of interest, and can further delineate its role in maintaining the oligomeric state of the protein. The entire procedure takes 2 d to complete.

Authors: Gupta, K; Li, J; Liko, I; Gault, J; Bechara, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Publishing Group
• Journal: Nature Protocols
• Volume: 13
• Issue: 5
• Pages: 1106–1120
• Publication date: 2018-04-26
• DOI: 10.1038/nprot.2018.014
• EISSN: 1750-2799
• ISSN: 1754-2189
• Pmid: 29700483
• Language: English