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      Proposal for a common nomenclature for fragment ions in mass spectra of lipids

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          Abstract

          Advances in mass spectrometry-based lipidomics have in recent years prompted efforts to standardize the annotation of the vast number of lipid molecules that can be detected in biological systems. These efforts have focused on cataloguing, naming and drawing chemical structures of intact lipid molecules, but have provided no guidelines for annotation of lipid fragment ions detected using tandem and multi-stage mass spectrometry, albeit these fragment ions are mandatory for structural elucidation and high confidence lipid identification, especially in high throughput lipidomics workflows. Here we propose a nomenclature for the annotation of lipid fragment ions, describe its implementation and present a freely available web application, termed ALEX 123 lipid calculator, that can be used to query a comprehensive database featuring curated lipid fragmentation information for more than 430,000 potential lipid molecules from 47 lipid classes covering five lipid categories. We note that the nomenclature is generic, extendable to stable isotope-labeled lipid molecules and applicable to automated annotation of fragment ions detected by most contemporary lipidomics platforms, including LC-MS/MS-based routines.

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          Orm family proteins mediate sphingolipid homeostasis

          Despite the essential roles of sphingolipids as both structural components of membranes and critical signalling molecules, we have a limited understanding of how cells sense and regulate their levels. Here we reveal the function in sphingolipid metabolism of the ORM/ORMDL genes, a conserved gene family that includes ORMDL3, which has recently been identified as a potential risk factor for childhood asthma. Starting from an unbiased functional genomic approach, we identify Orm proteins as negative regulators of sphingolipid synthesis that form a conserved complex with serine palmitoyltransferase, the first and rate-limiting enzyme in sphingolipid production. We also define a regulatory pathway in which phosphorylation of Orm proteins relieves their inhibitory activity when sphingolipid production is disrupted. Changes in ORM gene expression or mutations to their phosphorylation sites cause dysregulation of sphingolipid metabolism. Our work identifies the Orm proteins as critical mediators of sphingolipid homeostasis and raises the possibility that sphingolipid misregulation contributes to the development of childhood asthma.
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            An automated shotgun lipidomics platform for high throughput, comprehensive, and quantitative analysis of blood plasma intact lipids

            Blood plasma has gained protagonism in lipidomics studies due to its availability, uncomplicated collection and preparation, and informative readout of physiological status. At the same time, it is also technically challenging to analyze due to its complex lipid composition affected by many factors, which can hamper the throughput and/or lipidomics coverage. To tackle these issues, we developed a comprehensive, high throughput, and quantitative mass spectrometry-based shotgun lipidomics platform for blood plasma lipid analyses. The main hallmarks of this technology are (i) it is comprehensive, covering 22 quantifiable different lipid classes encompassing more than 200 lipid species; (ii) it is amenable to high-throughput, with less than 5 min acquisition time allowing the complete analysis of 200 plasma samples per day; (iii) it achieves absolute quantification, by inclusion of internal standards for every lipid class measured; (iv) it is highly reproducible, achieving an average coefficient of variation of <10% (intra-day), approx. 10% (inter-day), and approx. 15% (inter-site) for most lipid species; (v) it is easily transferable allowing the direct comparison of data acquired in different sites. Moreover, we thoroughly assessed the influence of blood stabilization with different anticoagulants and freeze-thaw cycles to exclude artifacts generated by sample preparation. Practical applications: This shotgun lipidomics platform can be implemented in different laboratories without compromising reproducibility, allowing multi-site studies and inter-laboratory comparisons. This possibility combined with the high-throughput, broad lipidomic coverage and absolute quantification are important aspects for clinical applications and biomarker research.
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              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.
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                Author and article information

                Contributors
                Role: InvestigationRole: MethodologyRole: Software
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: SoftwareRole: Visualization
                Role: InvestigationRole: MethodologyRole: Software
                Role: InvestigationRole: Methodology
                Role: Investigation
                Role: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: Supervision
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                21 November 2017
                2017
                : 12
                : 11
                : e0188394
                Affiliations
                [1 ] Department of Biochemistry and Molecular Biology, VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, Odense, Denmark
                [2 ] Institute of Computational Biotechnology, Graz University of Technology, Graz, Austria
                [3 ] Omics Center Graz, BioTechMed-Graz, Graz, Austria
                [4 ] Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Dortmund, Germany
                [5 ] Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
                Oregon State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/http://orcid.org/0000-0003-4963-0276
                Article
                PONE-D-17-25039
                10.1371/journal.pone.0188394
                5697860
                29161304
                5c784f11-bb76-4bd2-a882-7108d7cfbfa5
                © 2017 Pauling et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 July 2017
                : 20 October 2017
                Page count
                Figures: 8, Tables: 0, Pages: 21
                Product
                Funding
                Funded by: Villum Fonden (DK)
                Award ID: VKR023439
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100008398, Villum Fonden;
                Award ID: VKR023179
                Funded by: funder-id http://dx.doi.org/10.13039/501100003554, Lundbeckfonden;
                Award ID: R54-A5858
                Award Recipient :
                Funded by: Ministerium für Innovation Wissenschaft und Forschung des Landes Nordrhein-Westfalen
                Award Recipient :
                Funded by: Senatsverwaltung für Wirtschaft, Technologie und Forschung des Landes Berlin
                Award Recipient :
                Funded by: Bundesministerium für Bildung und Forschung, German Network for Bioinformatics Infrastructure
                Award ID: 031L0108A
                Award Recipient :
                This work was supported by the VILLUM Foundation (VKR023439; CSE; http://villumfonden.dk), the VILLUM Center for Bioanalytical Sciences (VKR023179; Department of Biochemistry and Molecular Biology; http://villumfonden.dk) and the Lundbeckfonden (R54-A5858; CSE; www.lundbeckfoundation.com). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Lipids
                Biology and Life Sciences
                Biochemistry
                Lipids
                Lipid Structure
                Biology and Life Sciences
                Molecular Biology
                Macromolecular Structure Analysis
                Lipid Analysis
                Biology and Life Sciences
                Biochemistry
                Lipids
                Lipid Metabolism
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Lipid Metabolism
                Physical Sciences
                Chemistry
                Chemical Compounds
                Hydrocarbons
                Physical Sciences
                Chemistry
                Chemical Physics
                Molecular Structure
                Physical Sciences
                Physics
                Chemical Physics
                Molecular Structure
                Physical Sciences
                Chemistry
                Chemical Reactions
                Biology and Life Sciences
                Biochemistry
                Lipids
                Sterols
                Custom metadata
                All relevant data are within the paper, its Supporting Information files and the web application ALEX123 ( http://alex123.info/ALEX123/MS.php).

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