BIH-Technologieplattform Metabolomik

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Development of a translational metabolomics platform at BIH

The 'integrative proteomics and metabolomics' research and technology platform is an integral part of the Berlin Institute for Medical Systems Biology (BIMSB) and develops the BIH Core Facility Metabolomics. We have planned the BIH Core Facility Metabolomics and have supported the reconstruction of House 64 at the MDC Campus Buch that is now hosting the BIH Core Facility Metabolomics.



Dr. Jennifer Kirwan


Dr. Chris Bielow
Alina Eisenberger
Fardad Ramezani (technical officer BIH Omics facility)




Dr. Stefan Kempa*: Leiter BIMSB Metabolomics Platform
Prof. Erich Wanker
: Proteomforschung und molekulare Mechanismen bei neurodegenerativen Erkrankungen
Prof. Mathias Treier
: Genetik metabolische und reproduktive Störungen

* derzeitiger Sprecher


Prof. Michael Schupp: Institut für Pharmakologie
Prof. Joachim Spranger
: Endokrinologie und Diabetologie, Sprecher CRU-Steuerungskomitee
Dr. Jan Lisec
: Metabolomics Charité, Clemens Schmitt Lab

Figure 1. Illustration of the established mass spectrometers and analytical techniques in relation to the metabolic network of a human cell.

The chemical space of metabolites spans a wide range of physicochemical properties. The size of the molecule, its polarity and complexity finally determines the separation method and its detectability by the mass spectrometer. Therefore, we have installed three different mass spectrometers coupled to several chromatographic systems to achieve a high coverage of the biochemical network of cells and organs (Figure 1).

  • GCxGC-EI-ToF, a gas chromatography based system that allows the measurement of small molecules (intermediates of the metabolism)
  • QQQ-LC-MS, a triple quadrupole mass spectrometer allows the measurement of small molecules, lipids and peptides (proteomics)
  • Q-Exactive (Orbitrap), a fourier transformation mass spectrometer that is used for proteomics, lipidomics and metabolomics analyses

Metabolomics in the field of personalized medicine

Assessing metabolism is of particular interest in context of the personalized medicine, because it represents both genetic predispositions and acute lifestyle influences. The metabolome adjusts on short time scales much faster than proteome, genome, and epigenetic settings. Paired sample series are essential for comparability but simultaneously offer more meaningful information about the acute physiological states and responses than other strategies that produce snapshots. Studying the dynamic responses to diagnostic challenges, for example similar to glucose tolerance tests but tailored to a disease of interest, might lead to sufficient knowledge for single sample diagnostics in the future. Personalized monitoring will reduce issues of comparability between people of different ages, lifestyles, diets, and gender through paired controls, and might provide an alternative route to biological understanding of diseases by allowing for targeted n=1 analyses, instead of the more common large n studies (Chen et al., 2012). We propose therefore a bench-at-bedside technology that could lead to a wealth of n=1 experiments analogous to studies of individuals with rare accidents or genetic mutations that have proven invaluable for a variety of medical fields. Due to the quantification of a great number of informative and interconnected metabolites of the central carbon metabolism that allow for personalized mechanistic understanding from minimal human blood samples, this platform, because of its robustness and reliability, promises insights and value beyond common biomarker studies.

To support the metabolomics studies we have developed a robotic system to facilitate the preparation of the required standard mixtures for metabolomics analyses and to perform the extraction and sample preparation procedures in an automatized way. This robotic system is a significant step towards lab automation, as it includes the handling of solid substances and liquids in a single system specifically designed for our workflows.

Figure 2. Scheme of the workflow of metabolomics analysis of a single drop of blood as established for the BIH core facility metabolomics.

Current Developments

Maui-VIA a data analysis tool for GC-MS data
is a software tool that enables a fast and precise analysis of GC-EI-MS metabolomics data1. The software-tool allows the automated analysis of our in house developed identification and quantification mixtures and includes additional measures for quality control. Early in 2015 we have organized the 1st GC-MS and MAUI-SILVIA user workshop incl. all members of the Kempa group and in addition members of BIMSB and MDC groups (Löwer, Jentsch, D. Müller, Spuler). The software tool is declared as invention at the MDC.

Figure 3. Pictures of the GC-MS introduction week (left) experimental part (right) software training.

Setup of comprehensive lipidome profiling

Lipids are an important class of metabolites that are crucial as structural components of biological membranes, signaling molecules and energy source. Lipids comprise the largest number among all classes of metabolites. In order to comprehensively analyze the lipidome of biological materials powerful methods are required. We use triple-quadrupol based parent ion and neutral loss scan methods as well as high resolution techniques to quantitatively measure the lipidome. A software tool for comprehensive data analysis is under development in context of the BIH metabolomics core. Bioinformatics analysis of the acquired mass spectrometry data will provide a comprehensive picture of both quantity and identify of the lipid species in a sample. The software required for this task is currently under development. We envision an integrated pipeline based on OpenMS software suite.

Figure 1: Lipid data analysis workflow overview.

Figure 2: Development of visualization tools. Mass spectrometry peaks are annotated with their database identifications. Ambiguous annotations are highlighted and theoretical isotope distributions are drawn for comparison.

Metabolomics pathfinder projects

In frame of the implementation of the BIH Core Facility Metabolomics, we have identified three metabolomics pathfinder projects.

  1. CRU @ ECRC Berlin Buch; MetaboNorm study. Together with the group of Friedrich Luft and Michael Boschmann the CRU at the ECRC we planned the profiling of a healthy cohort. Associated team: Tobias Opialla and Alina Eisenberger
  2. CRG Elucidating the proteostasis network to control Alzheimer’s disease. Associated team: Chris Bielow and Alina Eisenberger
  3. TRG Inflammation-induced skeletal muscle atrophy in critically ill patients: identification of molecular mechanisms and preventive therapies. Associated CRU: Intensive Care Unit, Virchow Campus. Associated team: Henning Kuich and Jenny Grobe


Kuich, P. H., Hoffmann, N. & Kempa, S. Maui-VIA: A User-Friendly Software for Visual Identification, Alignment, Correction, and Quantification of Gas Chromatography-Mass Spectrometry Data. Frontiers in bioengineering and biotechnology 2, 84, doi:10.3389/fbioe.2014.00084 (2014).