Maria Fedorova

Associate Professor for Lipidome Research Center of Membrane Biochemistry and Lipid Research, University Hospital and Faculty of Medicine, Carl Gustav Carus of TU Dresden.

https://fedorovalab.net/

BioSketch

Maria Fedorova studied Biochemistry at Saint-Petersburg State University, Russia and obtained her PhD at the Faculty of Chemistry and Mineralogy, Leipzig University, Germany. She worked as a Group Leader at the Institute of Bioanalytical Chemistry at the University of Leipzig. In 2021 Maria group moved to the Center for Membrane Biochemistry and Lipid Research, TU Dresden and in 2024 she became Associate Professor and Chair of Lipidome Research at the Faculty of Medicine, TU Dresden. Maria research is focused on understanding the mechanisms behind plasticity, adaptation and maladaptation of natural lipidomes in response to different stressors (metabolic, redox, etc). Using innovative mass spectrometry and bioinformatics solutions, her group looks at the lipid quality control machinery at subcellular, cellular and organismal levels.

Presentation

Mapping Lipid Metabolism Across Time and Space Using Mass Spectrometry

Modern mass spectrometry (MS)-based lipidomics provides an integrated view of lipid metabolism, ranging from quantitative lipid profiling to the characterization of the dynamic and spatial distribution of lipids in cells and complex tissue environments. In this presentation, I will highlight recent developments in our laboratory aimed at capturing the complexity and specificity of tissue lipidomes. Our approach combines quantitative deep lipidomics profiling using LC-MS/MS with in-depth lipid annotation and semi-absolute quantification to comprehensively characterize tissue-specific lipid compositions. To further enhance the precision of lipidome mapping, mass spectrometry imaging (MSI) technologies enable the spatial resolution of lipid distributions within tissues. Using MALDI-based MSI, supported by lipid annotations derived from LC–MS/MS analyses, we can map the topology of tissue lipid metabolism with high spatial precision, resolving metabolic features associated with specific cell types and tissue microenvironments. Finally, the application of biorthogonal labelling technologies combined with click chemistry-based charge-tagging enables highly sensitive tracing of lipid metabolic dynamics in living systems. This strategy allows us to move beyond the static snapshots typically provided by conventional lipidomics approaches and instead capture the dynamic remodelling of lipid metabolic and signalling pathways. /p>