Native MS-guided lipidomics to define endogenous lipid microenvironments of eukaryotic receptors and transporters

The mammalian membrane is composed of various eukaryotic lipids interacting with extensively post-translationally modified proteins. Probing interactions between these mammalian membrane proteins and their diverse and heterogeneous lipid cohort remains challenging. Recently, native mass spectrometry (MS) combined with bottom-up ‘omics’ approaches has provided valuable information to relate structural and functional lipids to membrane protein assemblies in eukaryotic membranes. Here we provide a step-by-step protocol to identify and provide relative quantification for endogenous lipids bound to mammalian membrane proteins and their complexes. Using native MS to guide our lipidomics strategies, we describe the necessary sample preparation steps, followed by native MS data acquisition, tailored lipidomics and data interpretation. We also highlight considerations for the integration of different levels of information from native MS and lipidomics and how to deal with the various challenges that arise during the experiments. This protocol begins with the preparation of membrane proteins from mammalian cells and tissues for native MS. The results enable not only direct assessment of copurified endogenous lipids but also determination of the apparent affinities of specific lipids. Detailed sample preparation for lipidomics analysis is also covered, along with comprehensive settings for liquid chromatography–MS analysis. This protocol is suitable for the identification and quantification of endogenous lipids, including fatty acids, sterols, glycerolipids, phospholipids and glycolipids and can be used to interrogate proteins from recombinant sources to native membranes. Native mass spectrometry can be combined with lipidomic experiments to determine the structural and functional lipids of receptor and transporter assemblies. This protocol describes how to use initial native mass spectrometry results to guide experimental design.