Previous and current research
Metabolomics, the field of science and technology concerned with small molecules, metabolites, and lipids, promises to advance our understanding of cell biology, physiology, and medicine. In recent years, metabolomics has progressed from cataloguing chemical structures to answering complex biomedical questions. Spatial and single-cell metabolomics have emerged as recent frontiers, focused on detecting, understanding, and interpreting metabolites and lipids in situ in their spatial context and at single-cell resolution. These research directions pose a multitude of challenges, yet promise to open novel avenues towards understanding metabolism at the new levels of cells, tissues, and organs, previously hidden in the world of bulk analyses.
Our team contributes to the emerging fields of spatial and single-cell metabolomics by developing experimental and computational methods. The team is highly interdisciplinary and brings together expertise in software development, computer science, mass spectrometry, metabolomics, and biology. We combine work in our wet lab, equipped with cutting-edge instrumentation for spatial metabolomics, with computational work involving bioinformatics, image analysis, and machine learning, with software development exploiting cutting-edge cloud and web software systems.
The underlying technology for our developments is imaging mass spectrometry, a powerful cutting-edge technology combining laser sampling at a resolution of 10 μm with mass spectrometry for molecular detection. Our current projects are concerned with finding metabolites in the dark matter of imaging mass spectrometry data, with establishing single-cell metabolomics integrating microscopy and imaging mass spectrometry, and with revealing metabolic states of single cells. Our applications focus on investigation of metabolic reprogramming of hepatocytes in non-alcoholic steatohepatitis and immune cells upon polarisation and activation, as well as on drug discovery and personalised oncology.
Future projects and goals
- Establishing methods for single-cell metabolomics of tissues.
- Revealing metabolic states with single-cell metabolomics and machine learning.
- Developing single-cell metabolomics methods for drug discovery and personalised therapy.
