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The beta-secretase, BACE, is a membrane spanning aspartic protease, which cleaves the amyloid precursor protein (APP) in the first step of proteolytic processing leading to the formation of the neurotoxic beta-amyloid peptide (Abeta). Previous results have suggested that the regulation of beta-secretase and BACE access to APP is lipid dependent, and involves lipid rafts. Using the baculovirus expression system, we have expressed recombinant human full-length BACE in insect cells and purified milligram amounts to homogeneity. We have studied partitioning of fluorophor-conjugated BACE between the liquid ordered and disordered phases in giant (10-150 mum) unilamellar vesicles, and found approximately 20% to associate with the raft-like, liquid-ordered phase; the fraction associated with liquid-ordered phase increased upon cross-linking of raft lipids. To examine involvement of individual lipid species in modulating BACE activity, we have reconstituted the purified BACE in large ( approximately 100 nm) unilamellar vesicles, and determined its specific activity in vesicles of various lipid compositions. We have identified 3 groups of lipids that stimulate proteolytic activity of BACE: 1) neutral glycosphingolipids (cerebrosides), 2) anionic glycerophospholipids, and 3) sterols (cholesterol).

Lipid rafts are nanoscopic assemblies of sphingolipids, cholesterol, and specific membrane proteins that contribute to lateral heterogeneity in eukaryotic membranes. Separation of artificial membranes into liquid-ordered (Lo) and liquid-disordered phases is regarded as a common model for this compartmentalization. However, tight lipid packing in Lo phases seems to conflict with efficient partitioning of raft-associated transmembrane (TM) proteins. To assess membrane order as a component of raft organization, we performed fluorescence spectroscopy and microscopy with the membrane probes Laurdan and C-laurdan. First, we assessed lipid packing in model membranes of various compositions and found cholesterol and acyl chain dependence of membrane order. Then we probed cell membranes by using two novel systems that exhibit inducible phase separation: giant plasma membrane vesicles [Baumgart et al. (2007) Proc Natl Acad Sci USA 104:3165-3170] and plasma membrane spheres. Notably, only the latter support selective inclusion of raft TM proteins with the ganglioside GM1 into one phase. We measured comparable small differences in order between the separated phases of both biomembranes. Lateral packing in the ordered phase of giant plasma membrane vesicles resembled the Lo domain of model membranes, whereas the GM1 phase in plasma membrane spheres exhibited considerably lower order, consistent with different partitioning of lipid and TM protein markers. Thus, lipid-mediated coalescence of the GM1 raft domain seems to be distinct from the formation of a Lo phase, suggesting additional interactions between proteins and lipids to be effective. [ABSTRACT FROM AUTHOR]

There are thousands of lipid species in living cells but we do not fully understand this diversity as it is not possible to pin down a specific function to each lipid species. Lipids have structural, metabolic and signaling functions. While signaling lipids can be understood and functionally characterized in a way similar to proteins, membrane lipids act collectively. This may have been one of the reasons for lipid neglect in the past. In order to understand the complexity of lipids in membranes, lipoproteins, body fluids, and organisms in general, we need to know the big picture which can only be delivered by modern lipidomic analyses. This has been increasingly appreciated mainly in the biomedical area. It is likely that interpretation of blood cell lipidomes will lead to the discovery of new biomarkers and lipid signatures of pathological states and cardiovascular disease risk, and so the era of HDL/LDL, TAG and cholesterol quantification may soon be over. But that is just one example. The motto of this year's Euro Fed Lipid Congress reads 'From lipidomics to industrial innovation'. Indeed with the advancement of mass-spectrometry and computational approaches to analyze and understand big data, lipidomics is becoming more interesting for clinical applications and industry. The shotgun methodology is so robust, comprehensive, fast and quantitative that it can be taken to the clinic, food R&D and into other applications. [ABSTRACT FROM AUTHOR]