Head of Facility

Dr. Jörg Büscher
Dr. Jörg Büscher
Phone:+49 761 5108 -640

Metabolomics Facility Service Website

Selected Publications

Buescher JM, Antoniewicz MR, Boros LG, Burgess SC, Brunengrabe, H, Clish CB, … Fendt S (2015)
A roadmap for interpreting 13C metabolite labeling patterns from cells.
Link H, Buescher JM & Sauer U (2012)
Targeted and quantitative metabolomics in bacteria.
Buescher JM, Liebermeister W, Jules M, Uhr M, Muntel J, Botella E, … Sauer U (2012)
Global Network Reorganization During Dynamic Adaptations of Bacillus subtilis Metabolism.

Metabolomics Facility

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Metabolomics Facility

All living cells are metabolically active, i.e. they take up substrates and use them to fuel a network of biochemical reactions. The intermediates of this network are called metabolites, their entirety is the metabolome. Metabolomics is the study of these chemical fingerprints. Like the genetic code, the metabolic network is highly conserved across species; therefore metabolomics can work for any biological model.

Metabolites directly reflect a cell’s physiological state, and thus integrates all levels of (genetic) regulation. Moreover, metabolomics is the ideal technology to dynamically observe the response to experimental perturbations, because metabolites can respond within seconds.

To capture the metabolic state of cells, the metabolomics core facility currently offers targeted and non-targeted quantification of metabolites using gas chromatography coupled to mass spectrometry (Agilent 7890 GC with 5977 MS) and ultra high pressure liquid chromatography coupled to mass spectrometry (Agilent 1290 Infinity II UHPLC with 6495 QQQ-MS). To quantify metabolic pathway usage we offer 13C tracing analyses, for which we also use our GCMS. All sample data is securely stored and organized in our database and we have a highly automated pipeline for the processing of GCMS and LCMS data.

The metabolomics core facility is more than an analytics lab. We assist users at every step of their metabolomics experiments including experimental design, sample prep, data processing, and data interpretation.

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