Decoding Distinct Ganglioside Patterns of Native and Differentiated Mesenchymal Stem Cells by a Novel Glycolipidomics Profiling Strategy

Katharina Hohenwallner; Nina Troppmair; Lisa Panzenboeck; Cornelia Kasper; Yasin El Abiead; Gunda Koellensperger; Leonida M Lamp; Jürgen Hartler; Dominik Egger; Evelyn Rampler

doi:10.1021/jacsau.2c00230

Decoding Distinct Ganglioside Patterns of Native and Differentiated Mesenchymal Stem Cells by a Novel Glycolipidomics Profiling Strategy

JACS Au. 2022 Oct 25;2(11):2466-2480. doi: 10.1021/jacsau.2c00230. eCollection 2022 Nov 28.

Authors

Katharina Hohenwallner^{1

2}, Nina Troppmair^{1

2}, Lisa Panzenboeck^{1

2}, Cornelia Kasper³, Yasin El Abiead¹, Gunda Koellensperger¹, Leonida M Lamp⁴, Jürgen Hartler^{4

5}, Dominik Egger³, Evelyn Rampler¹

Affiliations

¹ Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria.
² Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Vienna 1090, Austria.
³ Institute of Cell and Tissue Culture Technologies, University of Natural Resources and Life Sciences, Vienna 1190, Austria.
⁴ Institute of Pharmaceutical Sciences, University of Graz, Graz 8010, Austria.
⁵ Field of Excellence BioHealth - University of Graz, Graz 8010, Austria.

Abstract

Gangliosides are an indispensable glycolipid class concentrated on cell surfaces with a critical role in stem cell differentiation. Nonetheless, owing to the lack of suitable methods for scalable analysis covering the full scope of ganglioside molecular diversity, their mechanistic properties in signaling and differentiation remain undiscovered to a large extent. This work introduces a sensitive and comprehensive ganglioside assay based on liquid chromatography, high-resolution mass spectrometry, and multistage fragmentation. Complemented by an open-source data evaluation workflow, we provide automated in-depth lipid species-level and molecular species-level annotation based on decision rule sets for all major ganglioside classes. Compared to conventional state-of-the-art methods, the presented ganglioside assay offers (1) increased sensitivity, (2) superior structural elucidation, and (3) the possibility to detect novel ganglioside species. A major reason for the highly improved sensitivity is the optimized spectral readout based on the unique capability of two parallelizable mass analyzers for multistage fragmentation. We demonstrated the high-throughput universal capability of our novel analytical strategy by identifying 254 ganglioside species. As a proof of concept, 137 unique gangliosides were annotated in native and differentiated human mesenchymal stem cells including 78 potential cell-state-specific markers and 38 previously unreported gangliosides. A general increase of the ganglioside numbers upon differentiation was observed as well as cell-state-specific clustering based on the ganglioside species patterns. The combination of the developed glycolipidomics assay with the extended automated annotation tool enables comprehensive in-depth ganglioside characterization as shown on biological samples of interest. Our results suggest ganglioside patterns as a promising quality control tool for stem cells and their differentiation products. Additionally, we believe that our analytical workflow paves the way for probing glycolipid-based biochemical processes shedding light on the enigmatic processes of gangliosides and glycolipids in general.