24 research outputs found
Sex Dimorphism of Nonalcoholic Fatty Liver Disease (NAFLD) in Pparg-Null Mice.
Men with nonalcoholic fatty liver disease (NAFLD) are more exposed to nonalcoholic steatohepatitis (NASH) and liver fibrosis than women. However, the underlying molecular mechanisms of NALFD sex dimorphism are unclear. We combined gene expression, histological and lipidomic analyses to systematically compare male and female liver steatosis. We characterized hepatosteatosis in three independent mouse models of NAFLD, ob/ob and lipodystrophic fat-specific (PpargF <sup>Δ/Δ</sup> ) and whole-body PPARγ-null (Pparg <sup>Δ/Δ</sup> ) mice. We identified a clear sex dimorphism occurring only in Pparg <sup>Δ/Δ</sup> mice, with females showing macro- and microvesicular hepatosteatosis throughout their entire life, while males had fewer lipid droplets starting from 20 weeks. This sex dimorphism in hepatosteatosis was lost in gonadectomized Pparg <sup>Δ/Δ</sup> mice. Lipidomics revealed hepatic accumulation of short and highly saturated TGs in females, while TGs were enriched in long and unsaturated hydrocarbon chains in males. Strikingly, sex-biased genes were particularly perturbed in both sexes, affecting lipid metabolism, drug metabolism, inflammatory and cellular stress response pathways. Most importantly, we found that the expression of key sex-biased genes was severely affected in all the NAFLD models we tested. Thus, hepatosteatosis strongly affects hepatic sex-biased gene expression. With NAFLD increasing in prevalence, this emphasizes the urgent need to specifically address the consequences of this deregulation in humans
Characterisation of adipocyte-derived extracellular vesicle subtypes identifies distinct protein and lipid signatures for large and small extracellular vesicles
Extracellular vesicles (EVs) are biological vectors that can modulate the metabolism of target cells by conveying signalling proteins and genomic material. The level of EVs in plasma is significantly increased in cardiometabolic diseases associated with obesity, suggesting their possible participation in the development of metabolic dysfunction. With regard to the poor definition of adipocyte-derived EVs, the purpose of this study was to characterise both qualitatively and quantitatively EVs subpopulations secreted by fat cells. Adipocyte-derived EVs were isolated by differential centrifugation of conditioned media collected from 3T3-L1 adipocytes cultured for 24 h in serum-free conditions. Based on morphological and biochemical properties, as well as quantification of secreted EVs, we distinguished two subpopulations of adipocyte-derived EVs, namely small extracellular vesicles (sEVs) and large extracellular vesicles (lEVs). Proteomic analyses revealed that lEVs and sEVs exhibit specific protein signatures, allowing us not only to define novel markers of each population, but also to predict their biological functions. Despite similar phospholipid patterns, the comparative lipidomic analysis performed on these EV subclasses revealed a specific cholesterol enrichment of the sEV population, whereas lEVs were characterised by high amounts of externalised phosphatidylserine. Enhanced secretion of lEVs and sEVs is achievable following exposure to different biological stimuli related to the chronic low-grade inflammation state associated with obesity. Finally, we demonstrate the ability of primary murine adipocytes to secrete sEVs and lEVs, which display physical and biological characteristics similar to those described for 3T3-L1. Our study provides additional information and elements to define EV subtypes based on the characterisation of adipocyte-derived EV populations. It also underscores the need to distinguish EV subpopulations, through a combination of multiple approaches and markers, since their specific composition may cause distinct metabolic responses in recipient cells and tissues
Deciphering lipid structures based on platform-independent decision rule sets
We developed decision rule sets for Lipid Data Analyzer (LDA; http://genome.tugraz.at/lda2), enabling automated and reliable annotation of lipid species and their molecular structures in high-throughput data from chromatography-coupled tandem mass spectrometry. Platform independence was proven in various mass spectrometric experiments, comprising low- and high-resolution instruments and several collision energies. We propose that this independence and the capability to identify novel lipid molecular species render current state-of-the-art lipid libraries now obsolete
Balanced mTORC1 activity in oligodendrocytes is required for accurate CNS myelination
The mammalian target of rapamycin (mTOR) pathway integrates multiple signals and regulates crucial cell functions via the molecular complexes mTORC1 and mTORC2. These complexes are functionally dependent on their raptor (mTORC1) or rictor (mTORC2) subunits. mTOR has been associated with oligodendrocyte differentiation and myelination downstream of the PI3K/Akt pathway, but the functional contributions of individual complexes are largely unknown. We show, by oligodendrocyte-specific genetic deletion of Rptor and/or Rictor in the mouse, that CNS myelination is mainly dependent on mTORC1 function, with minor mTORC2 contributions. Myelin-associated lipogenesis and protein gene regulation are strongly reliant on mTORC1. We found that also oligodendrocyte-specific overactivation of mTORC1, via ablation of tuberous sclerosis complex 1 (TSC1), causes hypomyelination characterized by downregulation of Akt signaling and lipogenic pathways. Our data demonstrate that a delicately balanced regulation of mTORC1 activation and action in oligodendrocytes is essential for CNS myelination, which has practical overtones for understanding CNS myelin disorders
Quantitative analysis of N-acylphosphatidylethanolamine molecular species in rat brain using solid-phase extraction combined with reversed-phase chromatography and tandem mass spectrometry
10.1002/jssc.201600172Journal of Separation Science39132474-248
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Automated Annotation of Sphingolipids Including Accurate Identification of Hydroxylation Sites Using MSn Data.
Sphingolipids constitute a heterogeneous lipid category that is involved in many key cellular functions. For high-throughput analyses of sphingolipids, tandem mass spectrometry (MS/MS) is the method of choice, offering sufficient sensitivity, structural information, and quantitative precision for detecting hundreds to thousands of species simultaneously. While glycerolipids and phospholipids are predominantly non-hydroxylated, sphingolipids are typically dihydroxylated. However, species containing one or three hydroxylation sites can be detected frequently. This variability in the number of hydroxylation sites on the sphingolipid long-chain base and the fatty acyl moiety produces many more isobaric species and fragments than for other lipid categories. Due to this complexity, the automated annotation of sphingolipid species is challenging, and incorrect annotations are common. In this study, we present an extension of the Lipid Data Analyzer (LDA) "decision rule set" concept that considers the structural characteristics that are specific for this lipid category. To address the challenges inherent to automated annotation of sphingolipid structures from MS/MS data, we first developed decision rule sets using spectra from authentic standards and then tested the applicability on biological samples including murine brain and human plasma. A benchmark test based on the murine brain samples revealed a highly improved annotation quality as measured by sensitivity and reliability. The results of this benchmark test combined with the easy extensibility of the software to other (sphingo)lipid classes and the capability to detect and correctly annotate novel sphingolipid species make LDA broadly applicable to automated sphingolipid analysis, especially in high-throughput settings
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Automated Annotation of Sphingolipids Including Accurate Identification of Hydroxylation Sites Using MSn Data.
Sphingolipids constitute a heterogeneous lipid category that is involved in many key cellular functions. For high-throughput analyses of sphingolipids, tandem mass spectrometry (MS/MS) is the method of choice, offering sufficient sensitivity, structural information, and quantitative precision for detecting hundreds to thousands of species simultaneously. While glycerolipids and phospholipids are predominantly non-hydroxylated, sphingolipids are typically dihydroxylated. However, species containing one or three hydroxylation sites can be detected frequently. This variability in the number of hydroxylation sites on the sphingolipid long-chain base and the fatty acyl moiety produces many more isobaric species and fragments than for other lipid categories. Due to this complexity, the automated annotation of sphingolipid species is challenging, and incorrect annotations are common. In this study, we present an extension of the Lipid Data Analyzer (LDA) "decision rule set" concept that considers the structural characteristics that are specific for this lipid category. To address the challenges inherent to automated annotation of sphingolipid structures from MS/MS data, we first developed decision rule sets using spectra from authentic standards and then tested the applicability on biological samples including murine brain and human plasma. A benchmark test based on the murine brain samples revealed a highly improved annotation quality as measured by sensitivity and reliability. The results of this benchmark test combined with the easy extensibility of the software to other (sphingo)lipid classes and the capability to detect and correctly annotate novel sphingolipid species make LDA broadly applicable to automated sphingolipid analysis, especially in high-throughput settings
Phospholipid oxidation generates potent anti-inflammatory lipid mediators that mimic structurally related pro-resolving eicosanoids by activating Nrf2.
Exposure of biological membranes to reactive oxygen species creates a complex mixture of distinct oxidized phospholipid (OxPL) species, which contribute to the development of chronic inflammatory diseases and metabolic disorders. While the ability of OxPL to modulate biological processes is increasingly recognized, the nature of the biologically active OxPL species and the molecular mechanisms underlying their signaling remain largely unknown. We have employed a combination of mass spectrometry, synthetic chemistry, and immunobiology approaches to characterize the OxPL generated from the abundant phospholipid 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (PAPC) and investigated their bioactivities and signaling pathways in vitro and in vivo. Our study defines epoxycyclopentenones as potent anti-inflammatory lipid mediators that mimic the signaling of endogenous, pro-resolving prostanoids by activating the transcription factor nuclear factor E2-related factor 2 (Nrf2). Using a library of OxPL variants, we identified a synthetic OxPL derivative, which alleviated endotoxin-induced lung injury and inhibited development of pro-inflammatory T helper (Th) 1 cells. These findings provide a molecular basis for the negative regulation of inflammation by lipid peroxidation products and propose a novel class of highly bioactive compounds for the treatment of inflammatory diseases
Proteome profiling of extracellular vesicles derived from adipocytes reveal the presence of key metabolic proteins involved in obesity-associated metabolic dysfunctions
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