The research in Fedorova’s group is focused on development and implementation of lipidomics and bioinformatics solutions to address complexity and plasticity of lipid metabolism in variety of biological systems. By using modern, state-of-the-art high resolution mass spectrometry in combination with a wide range of separation methods we explore the complexity and dynamics of natural lipidomes to integrate these data for a holistic understanding of lipid metabolism. In particular, we are aiming to understand the pathophysiology of metabolic and inflammatory disorders, including obesity, insulin resistance, type II diabetes and liver pathologies. The question we want to answer is: how cellular, tissue or organism lipidomes react and adapt to the metabolic stress and at which point the adaptive metabolic response turns into the pathology?

Another focus of Dr. Fedorova’s research is the development and application of mass spectrometry-based methods for the analysis of the epilipidome, which is a subset of the lipidome formed by lipid modifications aiming to increase the regulatory capacity of biological systems. We are examining the role of modified lipids specifically in signalling processes, regulating physiological and pathological events at the cellular and organismal levels. In particular, the group is studying the role of modified lipids in ferroptosis, a newly described type of cell death implicated in degenerative diseases and cancer.

© Fedorova

Future Projects and Goals

We are aiming to find the molecular switches in lipid metabolic networks responsible for the transition from adaptive to maladaptive responses leading to dysregulation of lipid metabolism and development of human pathologies associated with dyslipidemia and chronic inflammation. This will allow not only to support mechanistic understanding of diseases etiology but will also provide access to intervention strategies.

Methodological and Technical Expertise

• Mass spectrometry based lipidomics/epilipidomics
• Lipid chemistry and biochemistry
• Software development using Python environment
• Multi-omics data integration
• Redox biochemistry