Literature DB >> 25409862

Principles and practice of lipidomics.

Frédéric M Vaz1, Mia Pras-Raves, Albert H Bootsma, Antoine H C van Kampen.   

Abstract

The technical advances in mass spectrometry, particularly the development of (ultra)-high-resolution/mass accuracy measurement capabilities in combination with refinement of soft ionization techniques, have increased the application and success of lipidomics to answer biological questions in relation to lipid metabolism. Together with other omics technologies, lipidomics has become an important tool to practice systems biology as lipids comprise a very significant part of the metabolome and play pleiotropic roles in cellular functions. As an increasing number of disorders are linked to lipid metabolism, lipidomics is used to search for biomarkers, understand disease mechanism and follow the efficacy of therapeutic options. This review provides a first introduction to the major methodological strategies currently used for mass spectrometry-based lipidomics and associated data pre-processing and analysis.

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Year:  2014        PMID: 25409862     DOI: 10.1007/s10545-014-9792-6

Source DB:  PubMed          Journal:  J Inherit Metab Dis        ISSN: 0141-8955            Impact factor:   4.982


  37 in total

Review 1.  Liquid chromatography-mass spectrometry based global metabolite profiling: a review.

Authors:  Georgios A Theodoridis; Helen G Gika; Elizabeth J Want; Ian D Wilson
Journal:  Anal Chim Acta       Date:  2011-11-04       Impact factor: 6.558

Review 2.  Analytical methods in lipidomics and their applications.

Authors:  Min Li; Li Yang; Yu Bai; Huwei Liu
Journal:  Anal Chem       Date:  2013-11-21       Impact factor: 6.986

3.  Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst.

Authors:  Jianguo Xia; David S Wishart
Journal:  Nat Protoc       Date:  2011-05-05       Impact factor: 13.491

Review 4.  An introduction to hybrid ion trap/time-of-flight mass spectrometry coupled with liquid chromatography applied to drug metabolism studies.

Authors:  Zhao-Ying Liu
Journal:  J Mass Spectrom       Date:  2012-12       Impact factor: 1.982

Review 5.  Informatics and computational strategies for the study of lipids.

Authors:  Matej Orešič
Journal:  Biochim Biophys Acta       Date:  2011-06-25

6.  Kinetic modelling of central carbon metabolism in Escherichia coli.

Authors:  Kirill Peskov; Ekaterina Mogilevskaya; Oleg Demin
Journal:  FEBS J       Date:  2012-09       Impact factor: 5.542

7.  Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data.

Authors:  Alla Karnovsky; Terry Weymouth; Tim Hull; V Glenn Tarcea; Giovanni Scardoni; Carlo Laudanna; Maureen A Sartor; Kathleen A Stringer; H V Jagadish; Charles Burant; Brian Athey; Gilbert S Omenn
Journal:  Bioinformatics       Date:  2011-11-30       Impact factor: 6.937

8.  Dynamic flux balance analysis of diauxic growth in Escherichia coli.

Authors:  Radhakrishnan Mahadevan; Jeremy S Edwards; Francis J Doyle
Journal:  Biophys J       Date:  2002-09       Impact factor: 4.033

9.  Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics.

Authors:  Vitali Matyash; Gerhard Liebisch; Teymuras V Kurzchalia; Andrej Shevchenko; Dominik Schwudke
Journal:  J Lipid Res       Date:  2008-02-16       Impact factor: 5.922

10.  A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions.

Authors:  Helen L Kotze; Emily G Armitage; Kieran J Sharkey; James W Allwood; Warwick B Dunn; Kaye J Williams; Royston Goodacre
Journal:  BMC Syst Biol       Date:  2013-10-23
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  13 in total

1.  A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source.

Authors:  Susanne B Breitkopf; Stéphane J H Ricoult; Min Yuan; Ying Xu; David A Peake; Brendan D Manning; John M Asara
Journal:  Metabolomics       Date:  2017-02-07       Impact factor: 4.290

2.  Development of cVSSI-APCI for the Improvement of Ion Suppression and Matrix Effects in Complex Mixtures.

Authors:  Madison E Pursell; Daud Sharif; Anthony DeBastiani; Chong Li; Sandra Majuta; Peng Li; Stephen J Valentine
Journal:  Anal Chem       Date:  2022-06-21       Impact factor: 8.008

3.  Applying a vernix caseosa based formulation accelerates skin barrier repair by modulating lipid biosynthesis.

Authors:  Walter A Boiten; Tineke Berkers; Samira Absalah; Jeroen van Smeden; Adriana P M Lavrijsen; Joke A Bouwstra
Journal:  J Lipid Res       Date:  2017-12-07       Impact factor: 5.922

Review 4.  Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences.

Authors:  Kui Yang; Xianlin Han
Journal:  Trends Biochem Sci       Date:  2016-09-20       Impact factor: 13.807

5.  Lipidomic analysis of fibroblasts from Zellweger spectrum disorder patients identifies disease-specific phospholipid ratios.

Authors:  Katharina Herzog; Mia L Pras-Raves; Martin A T Vervaart; Angela C M Luyf; Antoine H C van Kampen; Ronald J A Wanders; Hans R Waterham; Frédéric M Vaz
Journal:  J Lipid Res       Date:  2016-06-09       Impact factor: 5.922

Review 6.  The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges.

Authors:  Molly E McCue; Annette M McCoy
Journal:  Front Vet Sci       Date:  2017-11-16

7.  Plasma lipidomics as a diagnostic tool for peroxisomal disorders.

Authors:  Katharina Herzog; Mia L Pras-Raves; Sacha Ferdinandusse; Martin A T Vervaart; Angela C M Luyf; Antoine H C van Kampen; Ronald J A Wanders; Hans R Waterham; Frédéric M Vaz
Journal:  J Inherit Metab Dis       Date:  2017-12-05       Impact factor: 4.982

8.  The role of the clinician in the multi-omics era: are you ready?

Authors:  Clara D M van Karnebeek; Saskia B Wortmann; Maja Tarailo-Graovac; Mirjam Langeveld; Carlos R Ferreira; Jiddeke M van de Kamp; Carla E Hollak; Wyeth W Wasserman; Hans R Waterham; Ron A Wevers; Tobias B Haack; Ronald J A Wanders; Kym M Boycott
Journal:  J Inherit Metab Dis       Date:  2018-01-23       Impact factor: 4.982

9.  Serial-omics of P53-/-, Brca1-/- Mouse Breast Tumor and Normal Mammary Gland.

Authors:  Susanne B Breitkopf; Mateus De Oliveira Taveira; Min Yuan; Gerburg M Wulf; John M Asara
Journal:  Sci Rep       Date:  2017-11-06       Impact factor: 4.379

Review 10.  Is the clinical lipidomics a potential goldmine?

Authors:  Linlin Zhang; Xianlin Han; Xiangdong Wang
Journal:  Cell Biol Toxicol       Date:  2018-07-21       Impact factor: 6.691

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