Systems Biology of Metabolism
We are interested in cellular metabolism, how it drives cellular decisions and differentiation, and how it sustains pathological states in disease.
To address these questions, we develop and apply advanced techniques to monitor the activity of metabolic networks. Our approaches build largely on mass spectrometry (i.e. high-throughput and quantitative metabolomics, tracer studies, dynamic experiments) and computational analysis for data processing, mining, and integration. In particular, we strive to develop generally applicable, data-driven methods that can cope with the complexity of mammalian cells or dynamic systems.
Our toolbox is applied broadly on very different systems (microbes, worms, cell lines, mice, primary human cells and tissues, etc.) through a large network of collaborators in Academia and Industry. Read more
Zamboni lab: PhD Position available on cancer metabolism
Interested in understanding how cancer cells overcome metabolic inhibition? Read more
Three (!) IMSB students win ETH Prize for oustanding doctoral thesis
We are honored and proud to announce that George Rosenberger (Aebersold lab), Daniel Sévin (Sauer lab), and Andreas Kühne (Zamboni lab) won the prestigious ETH Silver Medal for Oustanding Doctoral Theses. Congratulations! Read more
Genome-wide landscape of gene-metabolite interactions charted for bacterium
How do gene (knock-outs) affect metabolite levels? We tested this systematically for > 3'800 genes in E. coli and found several suprises. Read more
Metabotypes of breast cancer cell lines revealed by non-targeted metabolomics
A metabolome and network centric analysis of 18 breast cancer cell lines reveals a fine-grained metabolic heterogeneity. The study will appear in a special issue of Metabolic Engineering devoted to cancer metabolism. We thank the team of our collaborator Prof. Almut Schulze (Würzburg). Read more
Nontargeted in vitro metabolomics for high-throughput identification of novel enzymes in Escherichia coli
About 15'000 high-throughput, non-targeted metabolomics analyses were acquired to study >1'200 functionally uncharacterized proteins. The study was just published by Daniel Sévin and co. in Nature Methods. Read more