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Development of metabolomics and fluxomics methods for metabolic drug target and toxicity elucidation using yeast


This project addresses a key issue in pharmaceutical research from a fundamental technological perspective: functional drug target identification and early detection of toxic side effects. When assessing metabolic functions, current methods such as proteomics or transcriptomics have inherently indirect readouts and are often not representative of the in vivo metabolic state. The aim of this multidisciplinary project is to monitored functional drug interactions with components in complex metabolic networks b y applying and developing metabolomics and fluxomics methods in combination with multivariate statistics and machine-learning. Thereby, we will conceptually extend the capability to observe metabolic network operation well beyond the limits of current technologies.

As a proof-of-concept, we focus on small molecule drugs that interfere with metabolism or its overlaying regulatory control network in the model eukaryote Saccharomyces cerevisiae. The hypothesis to be tested is whether multivariate statistical discrimination of mass spectrometry-detected nutritionally, pharmaceutically, or toxicologically relevant metabolic states have potential to conceptually improve early drug development. If successful, the novel approach is relevant for early in vivo characterization of drug target physiology and toxicology. While unicellular yeast is a pilot case, the approach can principally be extended to multi-cellular organisms and organs. Thus, this work has potential to improve the overall efficiency of European pharmaceutical research to treat human disease.

The project will be carried out at the ETH Institute of Molecular Systems Biology and the Centre for Systems Physiology and Metabolic Diseases under the supervision of Prof. U Sauer. The Centre offers a multidisciplinary research environment with world-class expertise in metabolomics, computer science, cell biology and pathology.

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