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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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FAIMS Shotgun Lipidomics for Enhanced Class- and Charge-State Separation Complemented by Automated Ganglioside

Katharina Hohenwallner1,2, Leonida M Lamp3, Liuyu Peng4

  • 1Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria.

Analytical Chemistry
|July 19, 2024
PubMed
Summary

We developed a rapid High Field Asymmetric Ion Mobility Spectrometry (FAIMS) shotgun lipidomics workflow and software for enhanced ganglioside detection. This method improves the identification of complex gangliosides and glycosphingolipids in biological samples.

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Area of Science:

  • Lipidomics
  • Analytical Chemistry
  • Glycobiology

Background:

  • Ganglioside analysis is challenging due to structural complexity and limited analytical tools.
  • Existing shotgun lipidomics methods often miss multiply charged ganglioside species.

Purpose of the Study:

  • To introduce a novel, rapid High Field Asymmetric Ion Mobility Spectrometry (FAIMS) shotgun lipidomics workflow for improved ganglioside detection.
  • To develop a dedicated software solution for automated ganglioside annotation and characterization.

Main Methods:

  • A 6-minute FAIMS shotgun lipidomics workflow was established, utilizing ramping compensation voltages for class- and charge-state separation.
  • A software extension for the Lipid Data Analyzer (LDA) was developed, integrating CID, HCD, and UVPD fragmentation data for automated annotation.
  • The workflow was applied to porcine brain extracts for ganglioside identification.

Main Results:

  • FAIMS enabled separation of ganglioside classes and charge states based on glycan structure and sialic acid content.
  • The new LDA software extension facilitated automated annotation of 29 ganglioside classes, including modifications.
  • 117 unique ganglioside species were identified in porcine brain extracts, with FAIMS enabling detection of multiply charged species.

Conclusions:

  • The FAIMS-driven shotgun lipidomics workflow significantly enhances ganglioside detection and characterization.
  • The integrated software provides automated annotation capabilities for complex lipid species.
  • This approach offers a powerful strategy for comprehensive analysis of gangliosides and glycosphingolipids.