Acute metabolic changes of plasma membrane (PM) lipids, such as those mediating signaling reactions, are rapidly compensated by homeostatic responses whose molecular basis is poorly understood. Here we show that the Extended-Synaptotagmins (E-Syts), ER proteins which function as PI(4,5)P2 and Ca2+-regulated tethers to the PM, participate in these responses. E-Syts transfer glycerolipids between bilayers in vitro and such transfer requires Ca2+ and their SMP domain, a lipid-harboring module. Genome edited cells lacking E-Syts do not exhibit abnormalities in the major glycerolipids at rest, but display enhanced and sustained accumulation of PM diacylglycerol (DAG) upon PI(4,5)P2 hydrolysis by PLC activation, which can be rescued by expression of E-Syt1, but not by mutant E-Syt1 lacking the SMP domain. The formation of E-Syts-dependent ER-PM tethers in response to stimuli that cleave PI(4,5)P2 and elevate Ca2+ may help reverse accumulation of DAG in the PM by transferring it to the ER for metabolic recycling.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

The trans-Golgi network (TGN) is the major sorting station in the secretory pathway of all eukaryotic cells. How the TGN sorts proteins and lipids to generate the enrichment of sphingolipids and sterols at the plasma membrane is poorly understood. To address this fundamental question in membrane trafficking, we devised an immunoisolation procedure for specific recovery of post-Golgi secretory vesicles transporting a transmembrane raft protein from the TGN to the cell surface in the yeast Saccharomyces cerevisiae. Using a novel quantitative shotgun lipidomics approach, we could demonstrate that TGN sorting selectively enriched ergosterol and sphingolipid species in the immunoisolated secretory vesicles. This finding, for the first time, indicates that the TGN exhibits the capacity to sort membrane lipids. Furthermore, the observation that the immunoisolated vesicles exhibited a higher membrane order than the late Golgi membrane, as measured by C-Laurdan spectrophotometry, strongly suggests that lipid rafts play a role in the TGN-sorting machinery.

Mass spectrometry-based shotgun lipidomics has enabled the quantitative and comprehensive assessment of cellular lipid compositions. The yeast Saccharomyces cerevisiae has proven to be a particularly valuable experimental system for studying lipid-related cellular processes. Here, by applying our shotgun lipidomics platform, we investigated the influence of a variety of commonly used growth conditions on the yeast lipidome, including glycerophospholipids, triglycerides, ergosterol as well as complex sphingolipids. This extensive dataset allowed for a quantitative description of the intrinsic flexibility of a eukaryotic lipidome, thereby providing new insights into the adjustments of lipid biosynthetic pathways. In addition, we established a baseline for future lipidomic experiments in yeast. Finally, flexibility of lipidomic features is proposed as a new parameter for the description of the physiological state of an organism.

Blood plasma has gained protagonism in lipidomics studies due to its availability, uncomplicated collection and preparation, and informative readout of physiological status. At the same time, it is also technically challenging to analyze due to its complex lipid composition affected by many factors, which can hamper the throughput and/or lipidomics coverage. To tackle these issues, we developed a comprehensive, high throughput, and quantitative mass spectrometry-based shotgun lipidomics platform for blood plasma lipid analyses. The main hallmarks of this technology are (i) it is comprehensive, covering 22 quantifiable different lipid classes encompassing more than 200 lipid species; (ii) it is amenable to high-throughput, with less than 5 min acquisition time allowing the complete analysis of 200 plasma samples per day; (iii) it achieves absolute quantification, by inclusion of internal standards for every lipid class measured; (iv) it is highly reproducible, achieving an average coefficient of variation of <10% (intra-day), approx. 10% (inter-day), and approx. 15% (inter-site) for most lipid species; (v) it is easily transferable allowing the direct comparison of data acquired in different sites. Moreover, we thoroughly assessed the influence of blood stabilization with different anticoagulants and freeze-thaw cycles to exclude artifacts generated by sample preparation.Practical applications: This shotgun lipidomics platform can be implemented in different laboratories without compromising reproducibility, allowing multi-site studies and inter-laboratory comparisons. This possibility combined with the high-throughput, broad lipidomic coverage and absolute quantification are important aspects for clinical applications and biomarker research.

The plasma membrane (PM) serves as the functional interface between a cell and its environment, hosting extracellular signal transduction and nutrient transport among a variety of other processes. To support this extensive functionality, PMs are organized into lateral domains, including ordered, lipid-driven assemblies termed lipid rafts. Although the general requirements for ordered domain formation are well established, how these domains are regulated by cell-endogenous mechanisms or exogenous perturbations has not been widely addressed. In this context, an intriguing possibility is that dietary fats can incorporate into membrane lipids to regulate the properties and physiology of raft domains. Here, we investigate the effects of polyunsaturated fats on the organization of membrane domains across a spectrum of membrane models, including computer simulations, synthetic lipid membranes, and intact PMs isolated from mammalian cells. We observe that the ω-3 polyunsaturated fatty acid docosahexaenoic acid is robustly incorporated into membrane lipids, and this incorporation leads to significant remodeling of the PM lipidome. Across model systems, docosahexaenoic acid-containing lipids enhance the stability of ordered raft domains by increasing the order difference between them and coexisting nonraft domains. The relationship between interdomain order disparity and the stability of phase separation holds for a spectrum of different perturbations, including manipulation of cholesterol levels and high concentrations of exogenous amphiphiles, suggesting it as a general feature of the organization of biological membranes. These results demonstrate that polyunsaturated fats affect the composition and organization of biological membranes, suggesting a potential mechanism for the extensive effects of dietary fat on health and disease.

Ontologies have proven very useful for capturing knowledge as a hierarchy of terms and their interrelationships. In biology a major challenge has been to construct ontologies of gene function given incomplete biological knowledge and inconsistencies in how this knowledge is manually curated. Here we show that large networks of gene and protein interactions in Saccharomyces cerevisiae can be used to infer an ontology whose coverage and power are equivalent to those of the manually curated Gene Ontology (GO). The network-extracted ontology (NeXO) contains 4,123 biological terms and 5,766 term-term relations, capturing 58% of known cellular components. We also explore robust NeXO terms and term relations that were initially not cataloged in GO, a number of which have now been added based on our analysis. Using quantitative genetic interaction profiling and chemogenomics, we find further support for many of the uncharacterized terms identified by NeXO, including multisubunit structures related to protein trafficking or mitochondrial function. This work enables a shift from using ontologies to evaluate data to using data to construct and evaluate ontologies.

Highlights d Brain-region-and cell-type-resolved lipidomic profiling d Definition of differences in lipid profiles of CNS cell types d Integration of lipid with protein expression profiles predicts lipid pathwaysd Aging alters brain lipid profiles with regional differences