TY - JOUR

T1 - Decoding Distinct Ganglioside Patterns of Native and Differentiated Mesenchymal Stem Cells by a Novel Glycolipidomics Profiling Strategy

AU - Hohenwallner, Katharina

AU - Troppmair, Nina

AU - Panzenboeck, Lisa

AU - Kasper, Cornelia

AU - El Abiead, Yasin

AU - Koellensperger, Gunda

AU - Lamp, Leonida M.

AU - Hartler, Jürgen

AU - Egger, Dominik

AU - Rampler, Evelyn

N1 - Funding Information: K.H. was financed by the Austrian Science Fonds (FWF) in course of the research group program (grant FG3), and open access funding was supported by the FWF. This work was supported by the University of Vienna, the Faculty of Chemistry, and the Vienna Metabolomics Center (VIME). We are grateful to PD Dr. med. Maike Keck for providing the MSC source tissue. The authors thank all members of the Rampler lab, Koellensperger lab (University of Vienna), Hartler lab (University of Graz), and Kasper lab (BOKU Vienna) for a great team spirit and scientific exchange. We further acknowledge our technicians Christoph Baumgartinger, Petra Voljecnik, and Julia Zoller for continuous lab support. We also thank Ilias Nikolits for the help with the graphical workflow representation and Richard Urban for cross-checking the database searches of the novel gangliosides.

PY - 2022/11/28

Y1 - 2022/11/28

N2 - 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.

AB - 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.

KW - automated annotation

KW - differentiation

KW - ganglioside

KW - glycolipidomics

KW - human

KW - LC-MS

KW - mass spectrometry

KW - mesenchymal stem cells

UR - http://www.scopus.com/inward/record.url?scp=85141399198&partnerID=8YFLogxK

U2 - 10.1021/jacsau.2c00230

DO - 10.1021/jacsau.2c00230

M3 - Article

AN - SCOPUS:85141399198

VL - 2

SP - 2466

EP - 2480

JO - Journal of the American Chemical Society

JF - Journal of the American Chemical Society

SN - 0002-7863

IS - 11

ER -