Figure 1: Surface mapping of two metabolites on the skin of female and male individuals. The models are overlaid with a molecular network in the background showing the structural relations between these and hundreds of other detected metabolites (Bouslimani A, et al., PNAS 2015). This was highlighted as an Image of the Year by Nature in 2015.
The Alexandrov team develops novel computational biology tools to reveal the spatial organisation of metabolic processes.
Previous and current research
Metabolomics, the study of the chemical fingerprints left by cellular processes, is considered as a crucial research area, promising 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. The next frontier now lies in spatial metabolomics, where the challenge is to map the whole metabolome with cellular and subcellular spatial resolution and to develop a mechanistic understanding of metabolic processes in space, at the levels of cell populations, organs, and organisms.
Our team contributes to the emerging field of spatial metabolomics by developing computational biology tools that enable imaging and functional interpretation of metabolites in tissue sections, agar plates, and cell cultures. The team is highly interdisciplinary and brings together expertise in mathematics, bioinformatics, and chemistry. We combine dry-lab research with the work in our wet lab equipped with cutting-edge instrumentation for metabolic imaging.
Figure 2: 3D spatial localisation of two metabolites (green, a rhamnolipid with an inhibitory function, and blue) secreted within the agar medium by the interacting colonies of Pseudomonas aeruginosa and Candida albicans (Watrous et al., ISME J. 2013).
Our tools exploit various analytical techniques based on mass spectrometry – in particular, high-resolution imaging mass spectrometry, which can generate 100 gigabytes of information-rich data in a single sample. Recently, we developed techniques for the molecular annotation of this large amount of data and applied it to various biological systems. We were able to visualise hundreds of metabolites with spatial resolution down to 5 μm in both 2D and 3D. Our applications include studying metabolic interactions of co-cultured microbial colonies, alterations in metabolic pathways due to therapy response in both cell cultures and model systems, and performing large-scale analysis of the surface of human skin.
Future projects and goals
- High-throughput metabolic imaging of biological tissues, agar plates and cell cultures in 2D and 3D.
- Spatial analysis of metabolic pathways and spatial pharmacometabolomics.
- Open bioinformatics engine for spatial metabolomics.