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.
Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. ...Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.
Lipidomics has become an indispensable method for the quantitative assessment of lipid metabolism in basic, clinical, and pharmaceutical research. It allows for the generation of information-dense ...datasets in a large variety of experimental setups and model organisms. Previous studies, mostly conducted in mice (Mus musculus), have shown a remarkable specificity of the lipid compositions of different cell types, tissues, and organs. However, a systematic analysis of the overall variation of the mouse lipidome is lacking. To fill this gap, in the present study, the effect of diet, sex, and genotype on the lipidomes of mouse tissues, organs, and bodily fluids has been investigated. Baseline quantitative lipidomes consisting of 796 individual lipid molecules belonging to 24 lipid classes are provided for 10 different sample types. Furthermore, the susceptibility of lipidomes to the tested parameters is assessed, providing insights into the organ-specific lipidomic plasticity and flexibility. This dataset provides a valuable resource for basic and pharmaceutical researchers working with murine models and complements existing proteomic and transcriptomic datasets. It will inform experimental design and facilitate interpretation of lipidomic datasets.
The family Flaviviridae includes viruses that have different virion structures and morphogenesis mechanisms. Most cellular and molecular studies have been so far performed with viruses of the ...Hepacivirus and Flavivirus genera. Here, we studied bovine viral diarrhea virus (BVDV), a member of the Pestivirus genus. We set up a method to purify BVDV virions and analyzed their morphology by electron microscopy and their protein and lipid composition by mass spectrometry. Cryo-electron microscopy showed near spherical viral particles displaying an electron-dense capsid surrounded by a phospholipid bilayer with no visible spikes. Most particles had a diameter of 50 nm and about 2% were larger with a diameter of up to 65 nm, suggesting some size flexibility during BVDV morphogenesis. Morphological and biochemical data suggested a low envelope glycoprotein content of BVDV particles, E1 and E2 being apparently less abundant than Erns. Lipid content of BVDV particles displayed a ~2.3 to 3.5-fold enrichment in cholesterol, sphingomyelin and hexosyl-ceramide, concomitant with a 1.5 to 5-fold reduction of all glycerophospholipid classes, as compared to lipid content of MDBK cells. Although BVDV buds in the endoplasmic reticulum, its lipid content differs from a typical endoplasmic reticulum membrane composition. This suggests that BVDV morphogenesis includes a mechanism of lipid sorting. Functional analyses confirmed the importance of cholesterol and sphingomyelin for BVDV entry. Surprisingly, despite a high cholesterol and sphingolipid content of BVDV envelope, E2 was not found in detergent-resistant membranes. Our results indicate that there are differences between the structure and molecular composition of viral particles of Flaviviruses, Pestiviruses and Hepaciviruses within the Flaviviridae family.
Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed ...at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays.
Membrane lipidome of an epithelial cell line Sampaio, Julio L; Gerl, Mathias J; Klose, Christian ...
Proceedings of the National Academy of Sciences - PNAS,
02/2011, Letnik:
108, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Tissue differentiation is an important process that involves major cellular membrane remodeling. We used Madin-Darby canine kidney cells as a model for epithelium formation and investigated the ...remodeling of the total cell membrane lipidome during the transition from a nonpolarized morphology to an epithelial morphology and vice versa. To achieve this, we developed a shotgun-based lipidomics workflow that enabled the absolute quantification of mammalian membrane lipidomes with minimal sample processing from low sample amounts. Epithelial morphogenesis was accompanied by a major shift from sphingomyelin to glycosphingolipid, together with an increase in plasmalogen, phosphatidylethanolamine, and cholesterol content, whereas the opposite changes took place during an epithelial-to-mesenchymal transition. Moreover, during polarization, the sphingolipids became longer, more saturated, and more hydroxylated as required to generate an apical membrane domain that serves as a protective barrier for the epithelial sheet.
The influenza virus (IFV) acquires its envelope by budding from host cell plasma membranes. Using quantitative shotgun mass spectrometry, we determined the lipidomes of the host Madin-Darby canine ...kidney cell, its apical membrane, and the IFV budding from it. We found the apical membrane to be enriched in sphingolipids (SPs) and cholesterol, whereas glycerophospholipids were reduced, and storage lipids were depleted compared with the whole-cell membranes. The virus membrane exhibited a further enrichment of SPs and cholesterol compared with the donor membrane at the expense of phosphatidylcholines. Our data are consistent with and extend existing models of membrane raft-based biogenesis of the apical membrane and IFV envelope.
Ten years ago, we wrote a Review on lipid rafts and signalling in the launch issue of Nature Reviews Molecular Cell Biology. At the time, this field was suffering from ambiguous methodology and ...imprecise nomenclature. Now, new techniques are deepening our insight into the dynamics of membrane organization. Here, we discuss how the field has matured and present an evolving model in which membranes are occupied by fluctuating nanoscale assemblies of sphingolipids, cholesterol and proteins that can be stabilized into platforms that are important in signalling, viral infection and membrane trafficking.
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.
We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, ...isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.
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