Sauer Group

Overview

The mission of our systems biology research in the Zamboni and Sauer labs is to identify and quantify the key regulation mechanisms that control cellular metabolism in microbes and mammalian cells (see Figure). The speciality of our interdisciplinary team of biologists, engineers, and computer scientists are high-throughput experimental technologies for quantitative metabolomics, 13C-based intracellular flux analysis, and dynamic GFP analysis in mini-scale cultivations. Different types of mathematical models are then used to quantitatively relate metabolomics, expression and proteomics data to the functional network output in terms of fluxes.

Close local collaboration between the IMSB labs metabolism (Sauer), quantitative analytics (Zamboni) and proteomics (Aebersold), and the ETH labs of computer science (Stelling), control engineering (Lygeros) and biochemistry (Peter) generate a highly interactive environment that focuses on the main model organisms E. coli and S. cerevisiae. In national and international collaborations we tackle systems-oriented, fundamental research questions on network structure, metabolic responses and controlling regulation events as well as applied research questions on metabolic engineering and cancer metabolism.

Figure 1: From molecular interactions to a functional network output
(Sauer U, Zamboni N (2008) Nat Biotechnol. 26:1090. PMID: 18846075)

References

• Heinemann M & Sauer U (2010). Systems biology of metabolism. Curr. Opin. Microbiol. 13: 337-343.
• Fendt SM, Oliveira AP, Christen S, Picotti P, Dechant RC, Sauer U (2010) Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast. Mol. Syst. Biol. 6:432.
• Zamboni N & Sauer U (2009). Novel biological insights through metabolomics and 13C-flux analysis. Curr. Opin. Microbiol. 12: 553-558.
• Sauer U, Heinemann M, Zamboni N (2007) Getting closer to the whole picture. Science 316:550.
• Schütz R, Küpfer L and Sauer U (2007) Systematic evaluation of objective functions for predicting intracellular fluxes in E. coli. Mol. Sys. Biol. 3:119
• Sauer U (2006) Metabolic networks in motion: 13C-based flux analysis. Mol. Sys. Biol. 2: 62