IsotopicLabelling: an R package for the analysis of MS isotopic patterns of labelled analytes.

Abstract Motivation Labelling experiments in biology usually make use of isotopically enriched substrates, with the two most commonly employed isotopes for metabolism being 2H and 13C. At the end of the experiment some metabolites will have incorporated the labelling isotope, to a degree that depends on the metabolic turnover. In order to propose a meaningful biological interpretation, it is necessary to estimate the amount of labelling, and one possible route is to exploit the fact that MS isotopic patterns reflect the isotopic distributions. Results We developed the IsotopicLabelling R package, a tool able to extract and analyze isotopic patterns from liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-MS (GC-MS) data relative to labelling experiments. This package estimates the isotopic abundance of the employed stable isotope (either 2H or 13C) within a specified list of analytes. Availability and Implementation The IsotopicLabelling R package is freely available at https://github.com/RuggeroFerrazza/IsotopicLabelling. Supplementary information Supplementary data are available at Bioinformatics online

New Analytical Methodologies at the Frontier of Cellular Lipidomics

Lipids were once thought to only be the building blocks of cell membranes and to serve as energy reserves. With time however, it became increasingly clear that they are actually involved in many more roles. Not surprisingly, the comprehensive characterisation of lipids in cells and tissues has experienced a growing interest worldwide, to the point that the term "lipidomics" was coined. This field is a subset of metabolomics, and the interesting point about these two sciences is that they are closest to the phenotype as compared to their "omics" counterparts (genomics, trascriptomics, ...), because metabolites and lipids are the end products of the –omics cascade. We have investigated mass spectrometry-based lipidomics from different perspectives: first of all, we have devised a targeted approach in which we have focused on sphingolipids and their perturbations. We started by working on neuronal cell cultures where we inhibited GBA, a key enzyme of the sphingolipid metabolism known to be one of the risk factors for Parkinson's disease. We found a significant sphingolipid unbalance characterised by an accumulation of glycosyl-ceramides. We then moved on by investigating the effects that LRRK2, an important and complex protein known to be related to autosomal-dominant forms of the disease, has on sphingolipids. We worked on mouse models, and we compared the sphingolipid profiles of wild-type (Lrrk2+/+) and knock-out (Lrrk2–/–) mice, finding a marked increase in ceramide levels and, more in general, in all lipids downstream of GBA. Such results hint to a possible interaction between LRRK2 and GBA, with LRRK2 playing a role in GBA regulation. In a second lipidomics investigation, we tried to understand whether or not anti-cancer treatments affect the lipid composition of tumours. Specifically, we concentrated on a common anti-angiogenic drug, whose aim is to starve cancer cells by inhibiting angiogenesis, a process required by the tumours to grow. We considered four different adenocarcinoma cell lines, which were subcutaneously inoculated into mice; the "control" animals received no treatment, whereas the "treated" ones were periodically given the drug. Interestingly, we found the treatment to have significant effects on the cancer lipidome, although the different lines responded unequally to the drug. Such results may reflect the huge heterogeneity of cancers and of individual responses to the treatment. Finally, we developed an informatics algorithm that deals with labelling experiments. The key point is that mass spectrometry measures isotopic patterns of analytes, which depend on the isotopic distribution of the elements; consequently, if an analyte incorporates the stable isotope employed in a labelling experiment, it will show a modified isotopic pattern. Our algorithm analyses such pattern, estimating the abundance of the incorporated label; we first tested it over carefully planned samples, and then we used it in a biochemical application where we wished to establish whether the rate of de novo lipogenesis is influenced by diet. This was accomplished by designing an experiment where mice were given partially deuterated water, while being fed different diets; we were able to ascertain that diet does indeed affect de novo lipogenesis, with the lowest rates occurring on fat-rich diets. We are confident that our tool may find useful applications, considering that stable isotope-based labelling experiments are becoming more and more popular

Potent Antifungal Properties of Dimeric Acylphloroglucinols from Hypericum mexicanum and Mechanism of Action of a Highly Active 3′Prenyl Uliginosin B

9openInternationalBothThe success of antifungal therapies is often hindered by the limited number of available drugs. To close the gap in the antifungal pipeline, the search of novel leads is of primary importance, and here the exploration of neglected plants has great promise for the discovery of new principles. Through bioassay-guided isolation, uliginosin B and five new dimeric acylphloroglucinols (uliginosins C-D, and 3′prenyl uliginosins B-D), besides cembrenoids, have been isolated from the lipophilic extract of Hypericum mexicanum. Their structures were elucidated by a combination of Liquid Chromatography - Mass Spectrometry LC-MS and Nuclear Magnetic Resonance (NMR) measurements. The compounds showed strong anti-Candida activity, also against fluconazole-resistant strains, with fungal growth inhibition properties at concentrations ranging from 3 to 32 µM, and reduced or absent cytotoxicity against human cell lines. A chemogenomic screen of 3′prenyl uliginosin B revealed target genes that are important for cell cycle regulation and cytoskeleton assembly in fungi. Taken together, our study suggests dimeric acylphloroglucinols as potential candidates for the development of alternative antifungal therapiesopenTocci, N.; Weil, T.; Perenzoni, D.; Moretto, M.; Nürk, N.; Madriñán, S.; Ferrazza, R.; Guella, G.; Mattivi, F.Tocci, N.; Weil, T.; Perenzoni, D.; Moretto, M.; Nürk, N.; Madriñán, S.; Ferrazza, R.; Guella, G.; Mattivi, F

Correction: Impaired cellular bioenergetics caused by GBA1 depletion sensitizes neurons to calcium overload

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Transcriptomic Analysis of Single Isolated Myofibers Identifies miR-27a-3p and miR-142-3p as Regulators of Metabolism in Skeletal Muscle

Summary: Skeletal muscle is composed of different myofiber types that preferentially use glucose or lipids for ATP production. How fuel preference is regulated in these post-mitotic cells is largely unknown, making this issue a key question in the fields of muscle and whole-body metabolism. Here, we show that microRNAs (miRNAs) play a role in defining myofiber metabolic profiles. mRNA and miRNA signatures of all myofiber types obtained at the single-cell level unveiled fiber-specific regulatory networks and identified two master miRNAs that coordinately control myofiber fuel preference and mitochondrial morphology. Our work provides a complete and integrated mouse myofiber type-specific catalog of gene and miRNA expression and establishes miR-27a-3p and miR-142-3p as regulators of lipid use in skeletal muscle. : Chemello et al. characterize coding mRNAs and non-coding microRNAs expressed by myofibers of hindlimb mouse muscles, identifying complex interactions between these molecules that modulate mitochondrial functions and muscle metabolism. They demonstrate that specific short non-coding RNAs influence the contractile fiber composition of skeletal muscles by modulating muscle metabolism. Keywords: single myofiber, skeletal muscle metabolism, mitochondria, miRNAs, lipid

LRRK2 deficiency impacts ceramide metabolism in brain

Mutations in LRRK2 gene cause inherited Parkinson's disease (PD) and variations around LRRK2 act as risk factor for disease. Similar to sporadic disease, LRRK2-linked cases show late onset and, typically, the presence of proteinaceous inclusions named Lewy bodies (LBs) in neurons. Recently, defects on ceramide (Cer) metabolism have been recognized in PD. In particular, heterozygous mutations in the gene encoding for glucocerebrosidase (GBA1), a lysosomal enzyme converting glucosyl-ceramides (Glc-Cer) into Cer, increase the risk of developing PD. Although several studies have linked LRRK2 with membrane-related processes and autophagic-lysosomal pathway regulation, whether this protein impinges on the Cer pathway has not been addressed. Here, using a targeted lipidomics approach, we report an altered sphingolipid composition in Lrrk2(-/-) mouse brains. In particular, we observe a significant increase of Cer levels in Lrrk2(-/-) mice and direct effects on GBA1. Collectively, our results suggest a link between LRRK2 and Cer metabolism, providing new insights into the possible role of this protein in sphingolipids metabolism, with implications for PD therapeutics

Rewiring of Lipid Metabolism and Storage in Ovarian Cancer Cells after Anti-VEGF Therapy

Anti-angiogenic therapy triggers metabolic alterations in experimental and human tumors, the best characterized being exacerbated glycolysis and lactate production. By using both Liquid Chromatography-Mass Spectrometry (LC-MS) and Nuclear Magnetic Resonance (NMR) analysis, we found that treatment of ovarian cancer xenografts with the anti-Vascular Endothelial Growth Factor (VEGF) neutralizing antibody bevacizumab caused marked alterations of the tumor lipidomic profile, including increased levels of triacylglycerols and reduced saturation of lipid chains. Moreover, transcriptome analysis uncovered up-regulation of pathways involved in lipid metabolism. These alterations were accompanied by increased accumulation of lipid droplets in tumors. This phenomenon was reproduced under hypoxic conditions in vitro, where it mainly depended from uptake of exogenous lipids and was counteracted by treatment with the Liver X Receptor (LXR)-agonist GW3965, which inhibited cancer cell viability selectively under reduced serum conditions. This multi-level analysis indicates alterations of lipid metabolism following anti-VEGF therapy in ovarian cancer xenografts and suggests that LXR-agonists might empower anti-tumor e ects of bevacizumab