The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells

The molecular study of fat cell development in the human body is essential for our
understanding of obesity and related diseases. Mesenchymal stem/stromal cells (MSC) are the ideal
source to study fat formation as they are the progenitors of adipocytes. In this work, we used human
MSCs, received from surgery waste, and differentiated them into fat adipocytes. The combination of
several layers of information coming from lipidomics, metabolomics and proteomics enabled network
analysis of the biochemical pathways in adipogenesis. Simultaneous analysis of metabolites, lipids,
and proteins in cell culture is challenging due to the compound’s chemical difference, so most studies
involve separate analysis with unimolecular strategies. In this study, we employed a multimolecular
approach using a two–phase extraction to monitor the crosstalk between lipid metabolism and
protein-based signaling in a single sample (~105
cells). We developed an innovative analytical
workflow including standardization with in-house produced 13C isotopically labeled compounds,
hyphenated high-end mass spectrometry (high-resolution Orbitrap MS), and chromatography (HILIC,
RP) for simultaneous untargeted screening and targeted quantification. Metabolite and lipid
concentrations ranged over three to four orders of magnitude and were detected down to the low fmol
(absolute on column) level. Biological validation and data interpretation of the multiomics workflow
was performed based on proteomics network reconstruction, metabolic modelling (MetaboAnalyst
4.0), and pathway analysis (OmicsNet). Comparing MSCs and adipocytes, we observed significant
regulation of different metabolites and lipids such as triglycerides, gangliosides, and carnitine with
113 fully reprogrammed pathways. The observed changes are in accordance with literature findings
dealing with adipogenic differentiation of MSC. These results are a proof of principle for the power
of multimolecular extraction combined with orthogonal LC-MS assays and network construction.
Considering the analytical and biological validation performed in this study, we conclude that the
proposed multiomics workflow is ideally suited for comprehensive follow-up studies on adipogenesis
and is fit for purpose for different applications with a high potential to understand the complex
pathophysiology of diseases.