| Autor: |
Hohenwallner K; Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria.; Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Vienna 1090, Austria., Lamp LM; Institute of Pharmaceutical Sciences, University of Graz, Graz 8010, Austria., Peng L; School of Chemistry, University of Melbourne, Parkville, Victoria 3010, Australia., Nuske M; School of Chemistry, University of Melbourne, Parkville, Victoria 3010, Australia., Hartler J; Institute of Pharmaceutical Sciences, University of Graz, Graz 8010, Austria.; Field of Excellence BioHealth, University of Graz, Graz 8010, Austria., Reid GE; School of Chemistry, University of Melbourne, Parkville, Victoria 3010, Australia.; Department of Biochemistry and Pharmacology, University of Melbourne, Parkville, Victoria 3010, Australia.; Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia., Rampler E; Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria.; Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Vienna 1090, Austria. |
| Abstrakt: |
The analysis of gangliosides is extremely challenging, given their structural complexity, lack of reference standards, databases, and software solutions. Here, we introduce a fast 6 min high field asymmetric ion mobility spectrometry (FAIMS) shotgun lipidomics workflow, along with a dedicated software solution for ganglioside detection. By ramping FAIMS compensation voltages, ideal ranges for different ganglioside classes were obtained. FAIMS revealed both class- and charge-state separation behavior based on the glycan headgroup moiety. The number of sialic acids attached to the glycan moiety correlates positively with their preferred charge states, i.e., trisialylated gangliosides were mainly present as [M - 3H] 3- ions, whereas [M - 4H] 4- and [M - 5H] 5- ions were observed for GQ1 and GP1. For data evaluation, we developed a shotgun/FAIMS extension for the open-source Lipid Data Analyzer (LDA), enabling automated annotation of gangliosides up to the molecular lipid species level. This extension utilized combined orthogonal fragmentation spectra from CID, HCD, and 213 nm UVPD ion activation methods and covers 29 ganglioside classes, including acetylated and fucosylated modifications. With our new workflow and software extension 117 unique gangliosides species were identified in porcine brain extracts. While conventional shotgun lipidomics favored the observation of singly charged ganglioside species, the utilization of FAIMS made multiply charged lipid species accessible, resulting in an increased number of detected species, primarily due to an improved signal-to-noise ratio arising from FAIMS charge state filtering. Therefore, this FAIMS-driven workflow, complemented by new software capabilities, offers a promising strategy for complex ganglioside and glycosphingolipid characterization in shotgun lipidomics. |
