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Altmaier, E. ; Römisch-Margl, W. ; Kastenmüller, G. ; Mewes, H.-W. ; Weinberger, K.M.* ; Suhre, K.

Targeted metabolomics for extensive phenotyping of mutant mice: db/db diabetes mice under rosiglitazone treatment.

Vortrag: FANG 2008, 25th January 2008, Rottach-Egern, Germany. (2008)
Metabolomics is a powerful tool for the identification of known and new disease-related perturbations in metabolic pathways. In mouse mutant phenotyping, it has an acute potential for the identification of cryptic phenotypes. Recent advances in high precision high throughput mass spectrometry have brought the field of to a point where quantitative targeted metabolomic measurements using ready-to-use analysis kits allow for automated high-throughput in-house screening for hundreds of different metabolites in large sets of biological samples. Today, the field of metabolomics is arguably at a point where transcriptomics was about five years ago, bringing with it the strong need for adapted bioinformatics tools and methods.   Here we describe results from such a systematic data analysis. Starting from a targeted quantitative characterization of more than 800 metabolites in blood plasma samples from healthy and diabetes mice under rosiglitazone treatment, we show that known and new metabolic phenotypes of diabetes and medication can be recovered in an objective manner. We find that concentrations of methylglutarylcarnitine are oppositely impacted by rosiglitazone treatment in the healthy and in the diabetes mouse groups. Analysis of ratios between metabolite concentrations dramatically reduces the noise in the dataset, allowing for the discovery of new potential biomarkers of diabetes, such some sphingomyelin compounds. Using a hierarchical clustering technique we identify functionally related groups of metabolites, indicating a diabetes-related link between lysophosphatidylcholine and phosphatidylcholine levels.   Our bioinformatics data analysis approach can be readily generalized to identify new mouse mutant phenotypes and related metabolic disorders. In particular, in the case of phenotype-less mutant mice, targeted metabolomics may allow to identify not immediately apparent mutant-specific changes in metabolic pathways. Based on such information, it is then possible to design nutritional or physical challenge experiments to bring out previously hidden phenotypes. We will discuss its potential in the light of the GSF metabolomics initiative and the role it may play in future mouse mutant phenotyping.
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Publikationstyp Sonstiges: Vortrag
Konferenztitel FANG 2008
Konferzenzdatum 25th January 2008
Konferenzort Rottach-Egern, Germany
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)