Elevated lipid class concentrations in females with anorexia nervosa before and after intensive weight restoration treatment-A lipidomics study.

OBJECTIVE: To study the plasma lipidome of patients with anorexia nervosa (AN) before and after weight restoration treatment and report associations with AN subtypes and oral contraceptive pill (OCP) usage. METHODS: Quantitative shotgun lipidomics analysis was used to study plasma lipids of 50 female patients with AN before and after weight restoration treatment and 50 healthy female controls (HC). The AN group was assessed with blood samples and questionnaires before and after weight restoration. RESULTS: In total we quantified 260 lipid species representing 26 lipid classes of which 13 lipid class concentrations were elevated in patients with AN at admission compared with HC. Lipid classes remained elevated after weight restoration treatment of 84 days (median; interquartile range 28), and only the concentration of the ceramide lipid class increased between pre- and post-treatment (p = .03), whereas lysophosphatidylcholine (LPC, p = .02), ether-linked Phosphatidylcholine (LPCO, p = .02), and lysophosphatidylethanolamine (LPE, p = .009) decreased. CONCLUSION: In AN, 13 out of 26 lipid class concentrations were elevated at admission and remained elevated post-treatment. Ceramides increased further between pre- and post-weight restoration treatment, which could be related to the rapid weight gain during re-nutrition. Further research is needed to elucidate the effects of weight restoration treatment on short- and long-term lipid profiles in individuals with AN. PUBLIC SIGNIFICANCE STATEMENT: Lipidomics research can increase the understanding of AN, a complex and potentially life-threatening eating disorder. By analyzing lipids, or fats, in the body, we can identify biological markers that may inform diagnosis and develop more effective treatments. This research can also shed light on the underlying mechanisms of the disorder, leading to a better understanding of the processes involved in eating behavior.

Profiling the Mammalian Lipidome by Quantitative Shotgun Lipidomics.

The emerging field of lipidomics presents the systems biology approach to identify and quantify the full lipid repertoire of cells, tissues, and organisms. The importance of the lipidome is demonstrated by a number of biological studies on dysregulation of lipid metabolism in human diseases such as cancer, diabetes, and neurodegenerative diseases. Exploring changes and regulations in the huge networks of lipids and their metabolic pathways requires a lipidomics methodology: advanced mass spectrometry that resolves the complexity of the lipidome. Here, we report a comprehensive protocol of quantitative shotgun lipidomics that enables identification and quantification of hundreds of molecular lipid species, covering a wide range of lipid classes, extracted from cultured mammalian cells.

Pathogenic variants of sphingomyelin synthase SMS2 disrupt lipid landscapes in the secretory pathway.

Sphingomyelin is a dominant sphingolipid in mammalian cells. Its production in the trans-Golgi traps cholesterol synthesized in the ER to promote formation of a sphingomyelin/sterol gradient along the secretory pathway. This gradient marks a fundamental transition in physical membrane properties that help specify organelle identify and function. We previously identified mutations in sphingomyelin synthase SMS2 that cause osteoporosis and skeletal dysplasia. Here, we show that SMS2 variants linked to the most severe bone phenotypes retain full enzymatic activity but fail to leave the ER owing to a defective autonomous ER export signal. Cells harboring pathogenic SMS2 variants accumulate sphingomyelin in the ER and display a disrupted transbilayer sphingomyelin asymmetry. These aberrant sphingomyelin distributions also occur in patient-derived fibroblasts and are accompanied by imbalances in cholesterol organization, glycerophospholipid profiles, and lipid order in the secretory pathway. We postulate that pathogenic SMS2 variants undermine the capacity of osteogenic cells to uphold nonrandom lipid distributions that are critical for their bone forming activity.

Unraveling membrane properties at the organelle-level with LipidDyn.

Cellular membranes are formed from different lipids in various amounts and proportions depending on the subcellular localization. The lipid composition of membranes is sensitive to changes in the cellular environment, and its alterations are linked to several diseases. Lipids not only form lipid-lipid interactions but also interact with other biomolecules, including proteins. Molecular dynamics (MD) simulations are a powerful tool to study the properties of cellular membranes and membrane-protein interactions on different timescales and resolutions. Over the last few years, software and hardware for biomolecular simulations have been optimized to routinely run long simulations of large and complex biological systems. On the other hand, high-throughput techniques based on lipidomics provide accurate estimates of the composition of cellular membranes at the level of subcellular compartments. Lipidomic data can be analyzed to design biologically relevant models of membranes for MD simulations. Similar applications easily result in a massive amount of simulation data where the bottleneck becomes the analysis of the data. In this context, we developed LipidDyn, a Python-based pipeline to streamline the analyses of MD simulations of membranes of different compositions. Once the simulations are collected, LipidDyn provides average properties and time series for several membrane properties such as area per lipid, thickness, order parameters, diffusion motions, lipid density, and lipid enrichment/depletion. The calculations exploit parallelization, and the pipeline includes graphical outputs in a publication-ready form. We applied LipidDyn to different case studies to illustrate its potential, including membranes from cellular compartments and transmembrane protein domains. LipidDyn is available free of charge under the GNU General Public License from https://github.com/ELELAB/LipidDyn.

Selective autophagy maintains centrosome integrity and accurate mitosis by turnover of centriolar satellites.

The centrosome is the master orchestrator of mitotic spindle formation and chromosome segregation in animal cells. Centrosome abnormalities are frequently observed in cancer, but little is known of their origin and about pathways affecting centrosome homeostasis. Here we show that autophagy preserves centrosome organization and stability through selective turnover of centriolar satellite components, a process we termed doryphagy. Autophagy targets the satellite organizer PCM1 by interacting with GABARAPs via a C-terminal LIR motif. Accordingly, autophagy deficiency results in accumulation of large abnormal centriolar satellites and a resultant dysregulation of centrosome composition. These alterations have critical impact on centrosome stability and lead to mitotic centrosome fragmentation and unbalanced chromosome segregation. Our findings identify doryphagy as an important centrosome-regulating pathway and bring mechanistic insights to the link between autophagy dysfunction and chromosomal instability. In addition, we highlight the vital role of centriolar satellites in maintaining centrosome integrity.