Identification and Quantification of Oxidized Lipids in LC-MS Lipidomics Data

Christoph A Krettler, Jürgen Hartler, Gerhard G Thallinger

Research output: Contribution to journalArticlepeer-review

Abstract

Changes in lipid homeostasis can lead to a plethora of diseases, raising the importance of reliable identification and measurement of lipids enabled by bioinformatics tools. However, due to the enormous diversity of lipids, most contemporary tools cover only a marginal range of lipid classes. To reduce such a shortcoming, this work extends the lipid species covered by Lipid Data Analyzer (LDA) to galactolipids and oxidized lipids. Appropriate mass lists were generated for MS1 identifications and the proprietary decision rule sets were extended for MS2 identifications of the novel lipid classes. Furthermore, LDA was extended to enable identification of oxidatively modified fatty acyl chains. With these extensions, LDA can reliably identify the most important galactolipids as well as oxidatively modified versions of the 22 previously implemented lipid classes. Comparison with other up to date lipidomics tools show that LDA has a better coverage of the newly implemented lipid species. The extended version of LDA provides researchers with a powerful platform to elucidate diseases caused by perturbations in the oxidized lipidome. LDA is freely available from https://genome.tugraz.at/lda.

Original languageEnglish
Pages (from-to)39-48
Number of pages10
JournalStudies in Health Technology and Informatics
Volume271
DOIs
Publication statusPublished - 23 Jun 2020

Keywords

  • Chromatography, Liquid
  • Homeostasis
  • Lipidomics
  • Lipids
  • Oxidation-Reduction
  • Tandem Mass Spectrometry

Fields of Expertise

  • Human- & Biotechnology
  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)

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