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Daqiang Pan   Mr.  Other 
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Daqiang Pan published an article in March 2018.
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Manfred Jung

256 shared publications

Institute of Pharmaceutical Sciences, University of Freiburg, Albertstraße 25, 79104 Freiburg im Breisgau, Germany

Nils Wiedemann

51 shared publications

Institute of Biochemistry and Molecular Biology, ZBMZ, Faculty of Medicine, University of Freiburg, 79104 Freiburg, Germany; BIOSS Centre for Biological Signalling Studies, University of Freiburg, 79104 Freiburg, Germany

Stefan Günther

48 shared publications

Institute of Pharmaceutical SciencesAlbert-Ludwigs-Universität Freiburg Hermann-Herder-Str. 9 79104 Freiburg Germany

S. U. Eisenhardt

46 shared publications

Universitätsklinikum Freiburg, Klinik für Plastische und Handchirurgie

Karin Schmidtkunz

24 shared publications

Institute of Pharmaceutical Sciences, Albert-Ludwigs-Universität Freiburg, Albertstraße 25, 79104 Freiburg, Germany

Publication Record
Distribution of Articles published per year 
(2016 - 2018)
Total number of journals
published in
Article 6 Reads 0 Citations Metabolic profiling of isolated mitochondria and cytoplasm reveals compartment-specific metabolic responses Daqiang Pan, Caroline Lindau, Simon Lagies, Nils Wiedemann, ... Published: 31 March 2018
Metabolomics, doi: 10.1007/s11306-018-1352-x
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Subcellular compartmentalization enables eukaryotic cells to carry out different reactions at the same time, resulting in different metabolite pools in the subcellular compartments. Thus, mutations affecting the mitochondrial energy metabolism could cause different metabolic alterations in mitochondria compared to the cytoplasm. Given that the metabolite pool in the cytosol is larger than that of other subcellular compartments, metabolic profiling of total cells could miss these compartment-specific metabolic alterations. To reveal compartment-specific metabolic differences, mitochondria and the cytoplasmic fraction of baker’s yeast Saccharomyces cerevisiae were isolated and subjected to metabolic profiling. Mitochondria were isolated through differential centrifugation and were analyzed together with the remaining cytoplasm by gas chromatography–mass spectrometry (GC–MS) based metabolic profiling. Seventy-two metabolites were identified, of which eight were found exclusively in mitochondria and sixteen exclusively in the cytoplasm. Based on the metabolic signature of mitochondria and of the cytoplasm, mutants of the succinate dehydrogenase (respiratory chain complex II) and of the FOF1-ATP-synthase (complex V) can be discriminated in both compartments by principal component analysis from wild-type and each other. These mitochondrial oxidative phosphorylation machinery mutants altered not only citric acid cycle related metabolites but also amino acids, fatty acids, purine and pyrimidine intermediates and others. By applying metabolomics to isolated mitochondria and the corresponding cytoplasm, compartment-specific metabolic signatures can be identified. This subcellular metabolomics analysis is a powerful tool to study the molecular mechanism of compartment-specific metabolic homeostasis in response to mutations affecting the mitochondrial metabolism. The online version of this article (10.1007/s11306-018-1352-x) contains supplementary material, which is available to authorized users.
CONFERENCE-ARTICLE 25 Reads 0 Citations Mitochondrial metabolomics reveals compartment-specific metabolic responses in yeast cells Daqiang Pan, Caroline Lindau, Simon Lagies, Stefan Günther, ... Published: 20 November 2017
Proceedings of The 2nd International Electronic Conference on Metabolomics, doi: 10.3390/iecm-2-04981
DOI See at publisher website ABS Show/hide abstract

Mutations in mitochondrial membrane proteins could cause physiological and metabolic alterations in mitochondria as well as in cytosol. In order to address the origin of these alterations, mitochondria and cytosol of yeast wild-type BY4741 and two mutants, sdh2Δ and atp4Δ, were isolated from whole cells. These three compartments, namely mitochondria, cytosol and whole cell, were analyzed by gas chromatography-mass spectrometry based metabolic profiling, identifying seventy-three metabolites altogether, from which sixteen or ten were not detected either in mitochondria or cytosol. Compartment-specific distribution and regulation of metabolites were observed, showing the responses to the deletions of sdh2 and atp4. Based on the metabolic signature in mitochondrial matrix and cytosol, both mutants can be discriminated from wild-type by principal component analysis. De letions of electron chain transport components, sdh2 and atp4, altered not only citrate cycle related metabolites, but also diverse metabolites including amino acids, fatty acids, purine and pyrimidine intermediates and others. By applying metabolomics to isolated mitochondria and cytosol, compartment-specific metabolic regulation can be identified, which is helpful in understanding the molecular mechanism of mitochondrial homeostasis in response to genetic mutations.

Article 0 Reads 2 Citations Metabolic Response to XD14 Treatment in Human Breast Cancer Cell Line MCF-7 Daqiang Pan, Michel Kather, Lucas Willmann, Manuel Schlimper... Published: 24 October 2016
International Journal of Molecular Sciences, doi: 10.3390/ijms17101772
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment. XD14 inhibits bromodomain and extra-terminal domain (BET) proteins (BRD2, BRD3, BRD4 and BRDT) and consequently suppresses cell proliferation. In this study, metabolic profiling reveals the molecular effects in the human breast cancer cell line MCF-7 (Michigan Cancer Foundation-7) treated by XD14. A three-day time series experiment with two concentrations of XD14 was performed. Gas chromatography-mass spectrometry (GC-MS) was applied for untargeted profiling of treated and non-treated MCF-7 cells. The gained data sets were evaluated by several statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Cell proliferation was strongly inhibited by treatment with 50 µM XD14. Samples could be discriminated by time and XD14 concentration using PLS-DA. From the 117 identified metabolites, 67 were significantly altered after XD14 treatment. These metabolites include amino acids, fatty acids, Krebs cycle and glycolysis intermediates, as well as compounds of purine and pyrimidine metabolism. This massive intervention in energy metabolism and the lack of available nucleotides could explain the decreased proliferation rate of the cancer cells.