Adipose tissue ATGL modifies the cardiac lipidome in pressure-overload-induced left ventricular failure

Adipose tissue lipolysis occurs during the development of heart failure as a consequence of chronic adrenergic stimulation. However, the impact of enhanced adipose triacylglycerol hydrolysis mediated by adipose triglyceride lipase (ATGL) on cardiac function is unclear. To investigate the role of adipose tissue lipolysis during heart failure, we generated mice with tissue-specific deletion of ATGL (atATGL-KO). atATGL-KO mice were subjected to transverse aortic constriction (TAC) to induce pressure-mediated cardiac failure. The cardiac mouse lipidome and the human plasma lipidome from healthy controls (n = 10) and patients with systolic heart failure (HFrEF, n = 13) were analyzed by MS-based shotgun lipidomics. TAC-induced increases in left ventricular mass (LVM) and diastolic LV inner diameter were significantly attenuated in atATGL-KO mice compared to wild type (wt) -mice. More importantly, atATGL-KO mice were protected against TAC-induced systolic LV failure. Perturbation of lipolysis in the adipose tissue of atATGL-KO mice resulted in the prevention of the major cardiac lipidome changes observed after TAC in wt-mice. Profound changes occurred in the lipid class of phosphatidylethanolamines (PE) in which multiple PE-species were markedly induced in failing wt-hearts, which was attenuated in atATGL-KO hearts. Moreover, selected heart failure-induced PE species in mouse hearts were also induced in plasma samples from patients with chronic heart failure. TAC-induced cardiac PE induction resulted in decreased PC/PE-species ratios associated with increased apoptotic marker expression in failing wt-hearts, a process absent in atATGL-KO hearts. Perturbation of adipose tissue lipolysis by ATGL-deficiency ameliorated pressure-induced heart failure and the potentially deleterious cardiac lipidome changes that accompany this pathological process, namely the induction of specific PE species. Non-cardiac ATGL-mediated modulation of the cardiac lipidome may play an important role in the pathogenesis of chronic heart failure

Shortening of membrane lipid acyl chains compensates for phosphatidylcholine deficiency in choline-auxotroph yeast

Phosphatidylcholine (PC) is an abundant membrane lipid component in most eukaryotes, including yeast, and has been assigned multiple functions in addition to acting as building block of the lipid bilayer. Here, by isolating S. cerevisiae suppressor mutants that exhibit robust growth in the absence of PC, we show that PC essentiality is subject to cellular evolvability in yeast. The requirement for PC is suppressed by monosomy of chromosome XV or by a point mutation in the ACC1 gene encoding acetyl-CoA carboxylase. Although these two genetic adaptations rewire lipid biosynthesis in different ways, both decrease Acc1 activity, thereby reducing average acyl chain length. Consistently, soraphen A, a specific inhibitor of Acc1, rescues a yeast mutant with deficient PC synthesis. In the aneuploid suppressor, feedback inhibition of Acc1 through acyl-CoA produced by fatty acid synthase (FAS) results from upregulation of lipid synthesis. The results show that budding yeast regulates acyl chain length by fine-tuning the activities of Acc1 and FAS and indicate that PC evolved by benefitting the maintenance of membrane fluidity

Eisosome proteins assemble into a membrane scaffold

Membrane organization by eisosomes is mediated by self-assembly of its main components into a membrane-bound protein scaffold with lipid-binding specificity

Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population-Ascertained Hyperlipidemias

Background-We asked whether, after excluding familial hypercholesterolemia, individuals with high low-density lipoprotein cholesterol (LDL-C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population-based hyperlipidemias. Methods and Results-We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (>2 first-degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias (LDL-C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta-analysis of the hyperlipidemic families and the population cohort (high LDL-C: hazard ratio, 1.74 [95% CI, 1.48-2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI 1.09-1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid-lowering medication. In lipidomic profiling, high LDL-C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P-value range 0.038-2.3x 10(-56)). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population (LDL-C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts). Conclusions-Hyperlipidemias with family history conferred similar coronary artery disease risk as population-based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL-C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.Peer reviewe

Flexibility of a Eukaryotic Lipidome – Insights from Yeast Lipidomics

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

Segregation of sphingolipids and sterols during formation of secretory vesicles at the trans-Golgi network

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

Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers

https://deepblue.lib.umich.edu/bitstream/2027.42/138963/1/12987_2017_Article_71.pd

Comprehensive and quantitative analysis of white and brown adipose tissue by shotgun lipidomics

Objective: Shotgun lipidomics enables an extensive analysis of lipids from tissues and fluids. Each specimen requires appropriate extraction and processing procedures to ensure good coverage and reproducible quantification of the lipidome. Adipose tissue (AT) has become a research focus with regard to its involvement in obesity-related pathologies. However, the quantification of the AT lipidome is particularly challenging due to the predominance of triacylglycerides, which elicit high ion suppression of the remaining lipid classes. Methods: We present a new and validated method for shotgun lipidomics of AT, which tailors the lipid extraction procedure to the target specimen and features high reproducibility with a linear dynamic range of at least 4 orders of magnitude for all lipid classes. Results: Utilizing this method, we observed tissue-specific and diet-related differences in three AT types (brown, gonadal, inguinal subcutaneous) from lean and obese mice. Brown AT exhibited a distinct lipidomic profile with the greatest lipid class diversity and responded to high-fat diet by altering its lipid composition, which shifted towards that of white AT. Moreover, diet-induced obesity promoted an overall remodeling of the lipidome, where all three AT types featured a significant increase in longer and more unsaturated triacylglyceride and phospholipid species. Conclusions: The here presented method facilitates reproducible systematic lipidomic profiling of AT and could be integrated with further –omics approaches used in (pre-) clinical research, in order to advance the understanding of the molecular metabolic dynamics involved in the pathogenesis of obesity-associated disorders. Keywords: Shotgun mass spectrometry, Lipidomics, Adipose tissue, Method validation, Lipid extraction, Mouse, Chow and high-fat diet, Lipid remodelin

A gene ontology inferred from molecular networks

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