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  • 101.
    Vogel, Katharina U
    et al.
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Edelmann, Stephanie L
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Jeltsch, Katharina M
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Bertossi, Arianna
    Max Planck Institute of Biochemistry, Martinsried, Germany.
    Heger, Klaus
    Max Planck Institute of Biochemistry, Martinsried, Germany.
    Heinz, Gitta A
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Zöller, Jessica
    Institute for Virology, Technische Universität München/Helmholtz Zentrum München, Munich, Germany.
    Warth, Sebastian C
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Hoefig, Kai P
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Lohs, Claudia
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Neff, Frauke
    Institute of Pathology, Helmholtz Zentrum München, Neuherberg, Germany.
    Kremmer, Elisabeth
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany.
    Schick, Joel
    Institute of Developmental Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
    Repsilber, Dirk
    Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany.
    Geerlof, Arie
    Institute of Structural Biology, Helmholtz Zentrum München, Neuherberg, Germany.
    Blum, Helmut
    Laboratory for Functional Genome Analysis, Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany.
    Wurst, Wolfgang
    Institute of PAthology, Helmholtz Zentrum München, Neuherberg, Germany; Max-Planck-Institute of Psychiatry, Munich, Germany; Technische Universität München, Lehrstuhl für Entwicklungsgenetik c/o Helmholtz Zentrum München, Neuherberg, Germany; Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Munich, Germany.
    Heikenwälder, Mathias
    Institute for Virology, Technische Universität München/Helmholtz Zentrum München, Munich, Germany.
    Schmidt-Supprian, Marc
    Max Planck Institute of Biochemistry, Martinsried, Germany.
    Heissmeyer, Vigo
    Institute of Molecular Immunology, Helmholtz Zentrum München, Munich, Germany; Institute for Immunology, Ludwig-Maximilians-Universität München, Munich, Germany.
    Roquin paralogs 1 and 2 redundantly repress the Icos and Ox40 costimulator mRNAs and control follicular helper T cell differentiation2013In: Immunity, ISSN 1074-7613, E-ISSN 1097-4180, Vol. 38, no 4, p. 655-68Article in journal (Refereed)
    Abstract [en]

    The Roquin-1 protein binds to messenger RNAs (mRNAs) and regulates gene expression posttranscriptionally. A single point mutation in Roquin-1, but not gene ablation, increases follicular helper T (Tfh) cell numbers and causes lupus-like autoimmune disease in mice. In T cells, we did not identify a unique role for the much lower expressed paralog Roquin-2. However, combined ablation of both genes induced accumulation of T cells with an effector and follicular helper phenotype. We showed that Roquin-1 and Roquin-2 proteins redundantly repressed the mRNA of inducible costimulator (Icos) and identified the Ox40 costimulatory receptor as another shared mRNA target. Combined acute deletion increased Ox40 signaling, as well as Irf4 expression, and imposed Tfh differentiation on CD4(+) T cells. These data imply that both proteins maintain tolerance by preventing inappropriate T cell activation and Tfh cell differentiation, and that Roquin-2 compensates in the absence of Roquin-1, but not in the presence of its mutated form.

  • 102.
    Warsow, Gregor
    et al.
    Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany; Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany; Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany .
    Greber, Boris
    Department of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, Münster, Germany .
    Falk, Steffi S I
    Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany .
    Harder, Clemens
    Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany .
    Siatkowski, Marcin
    Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany; DZNE, German Center for Neurodegenerative Disorders, Rostock, Germany .
    Schordan, Sandra
    Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany .
    Som, Anup
    Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany .
    Endlich, Nicole
    Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany .
    Schöler, Hans
    Department of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, Münster, Germany; Medical Faculty, University of Münster, Münster, Germany .
    Repsilber, Dirk
    Research Unit Biomathematics and Bioinformatics, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany .
    Endlich, Karlhans
    Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany .
    Fuellen, Georg
    Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany .
    ExprEssence: revealing the essence of differential experimental data in the context of an interaction/regulation net-work2010In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 4, p. 164-, article id 164Article in journal (Refereed)
    Abstract [en]

    Background: Experimentalists are overwhelmed by high-throughput data and there is an urgent need to condense information into simple hypotheses. For example, large amounts of microarray and deep sequencing data are becoming available, describing a variety of experimental conditions such as gene knockout and knockdown, the effect of interventions, and the differences between tissues and cell lines.

    Results: To address this challenge, we developed a method, implemented as a Cytoscape plugin called ExprEssence. As input we take a network of interaction, stimulation and/or inhibition links between genes/proteins, and differential data, such as gene expression data, tracking an intervention or development in time. We condense the network, highlighting those links across which the largest changes can be observed. Highlighting is based on a simple formula inspired by the law of mass action. We can interactively modify the threshold for highlighting and instantaneously visualize results. We applied ExprEssence to three scenarios describing kidney podocyte biology, pluripotency and ageing: 1) We identify putative processes involved in podocyte (de-)differentiation and validate one prediction experimentally. 2) We predict and validate the expression level of a transcription factor involved in pluripotency. 3) Finally, we generate plausible hypotheses on the role of apoptosis, cell cycle deregulation and DNA repair in ageing data obtained from the hippocampus.

    Conclusion: Reducing the size of gene/protein networks to the few links affected by large changes allows to screen for putative mechanistic relationships among the genes/proteins that are involved in adaptation to different experimental conditions, yielding important hypotheses, insights and suggestions for new experiments. We note that we do not focus on the identification of 'active subnetworks'. Instead we focus on the identification of single links (which may or may not form subnetworks), and these single links are much easier to validate experimentally than submodules. ExprEssence is available at http://sourceforge.net/projects/expressence/.

  • 103.
    Weiner, January
    et al.
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Parida, Shreemanta K
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Maertzdorf, Jeroen
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Black, Gillian F
    Department of Biomedical Sciences, University of Stellenbosch, Cape Town, South Africa.
    Repsilber, Dirk
    Biomathematics/Bioinformatics Group, Genetics and Biometry, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Telaar, Anna
    Biomathematics/Bioinformatics Group, Genetics and Biometry, Leibniz Institute for Farm Animal Biology, FBN, Dummerstorf, Germany.
    Mohney, Robert P
    Metabolon Inc., Durham NC, USA.
    Arndt-Sullivan, Cordelia
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Ganoza, Christian A
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Faé, Kellen C
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Walzl, Gerhard
    Department of Biomedical Sciences, University of Stellenbosch, Cape Town, South Africa.
    Kaufmann, Stefan H E
    Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany.
    Biomarkers of inflammation, immunosuppression and stress with active disease are revealed by metabolomic profiling of tuberculosis patients2012In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 7, p. e40221-, article id e40221Article in journal (Refereed)
    Abstract [en]

    Although tuberculosis (TB) causes more deaths than any other pathogen, most infected individuals harbor the pathogen without signs of disease. We explored the metabolome of >400 small molecules in serum of uninfected individuals, latently infected healthy individuals and patients with active TB. We identified changes in amino acid, lipid and nucleotide metabolism pathways, providing evidence for anti-inflammatory metabolomic changes in TB. Metabolic profiles indicate increased activity of indoleamine 2,3 dioxygenase 1 (IDO1), decreased phospholipase activity, increased abundance of adenosine metabolism products, as well as indicators of fibrotic lesions in active disease as compared to latent infection. Consistent with our predictions, we experimentally demonstrate TB-induced IDO1 activity. Furthermore, we demonstrate a link between metabolic profiles and cytokine signaling. Finally, we show that 20 metabolites are sufficient for robust discrimination of TB patients from healthy individuals. Our results provide specific insights into the biology of TB and pave the way for the rational development of metabolic biomarkers for TB.

  • 104. Welander, Edward
    et al.
    Åström, Maria
    Örebro University, School of Medical Sciences. Örebro University, School of Health Sciences.
    Enonge Fotabe, Leslie
    Kardeby, Caroline
    Örebro University, School of Medical Sciences.
    Tina, Elisabet
    Örebro University, School of Medical Sciences.
    Elgbratt, Kristina
    Örebro University, School of Health Sciences.
    Pourlofti, Arvid
    Abawi, Akram
    Romild, Alma
    Kruse, Robert
    Örebro University, School of Medical Sciences.
    Repsilber, Dirk
    Örebro University, School of Medical Sciences.
    Crafoord, Jakob
    Ahlstrand, Erik
    Ivarsson, Mikael
    Örebro University, School of Health Sciences.
    Integrated analysis indicates reciprocal immune response dysregulations between bone marrow multipotent stromal cells and granulocytes at the mRNA but not at the protein level in myelofibrosis2018Conference paper (Refereed)
  • 105.
    Wittenburg, Dörte
    et al.
    Genetics and Biometry, Leibniz Institute for Farm Animal Biology, Dummersdorf, Germany.
    Melzer, Nina
    Genetics and Biometry, Leibniz Institute for Farm Animal Biology, Dummersdorf, Germany.
    Reinsch, Norbert
    Genetics and Biometry, Leibniz Institute for Farm Animal Biology, Dummersdorf, Germany.
    Repsilber, Dirk
    Genetics and Biometry, Leibniz Institute for Farm Animal Biology, Dummersdorf, Germany.
    Milk metabolites and their genetic variability2012In: Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science: Bratislava, Slovakia, 27 - 31 August 2012, Wageningen: Wageningen Academic Publishers, 2012, p. 94-94Conference paper (Refereed)
  • 106.
    Wittenburg, Dörte
    et al.
    Institute for Genetics and Biometry, Unit Biomathematics and Bioinformatics, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany .
    Melzer, Nina
    Institute for Genetics and Biometry, Unit Biomathematics and Bioinformatics, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany .
    Willmitzer, Lothar
    Max Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Lisec, Jan
    Max Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Kesting, U
    Landeskontrollverband für Leistungs, Qualitätsprüfung Mecklenburg-Vorpommern e.V. (LKV), Güstrow, Germany .
    Reinsch, Norbert
    Institute for Genetics and Biometry, Unit Biomathematics and Bioinformatics, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany .
    Repsilber, Dirk
    Institute for Genetics and Biometry, Unit Biomathematics and Bioinformatics, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany .
    Milk metabolites and their genetic variability2013In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 96, no 4, p. 2557-69Article in journal (Refereed)
    Abstract [en]

    The composition of milk is crucial to evaluate milk performance and quality measures. Milk components partly contribute to breeding scores, and they can be assessed to judge metabolic and energy status of the cow as well as to serve as predictive markers for diseases. In addition to the milk composition measures (e.g., fat, protein, lactose) traditionally recorded during milk performance test via infrared spectroscopy, novel techniques, such as gas chromatography-mass spectrometry, allow for a further analysis of milk into its metabolic components. Gas chromatography-mass spectrometry is suitable for measuring several hundred metabolites with high throughput, and thus it is applicable to study sources of genetic and nongenetic variation of milk metabolites in dairy cows. Heritability and mode of inheritance of metabolite measurements were studied in a linear mixed model approach including expected (pedigree) and realized (genomic) relationship between animals. The genetic variability of 190 milk metabolite intensities was analyzed from 1,295 cows held on 18 farms in Mecklenburg-Western Pomerania, Germany. Besides extensive pedigree information, genotypic data comprising 37,180 single nucleotide polymorphism markers were available. Goodness of fit and significance of genetic variance components based on likelihood ratio tests were investigated with a full model, including marker- and pedigree-based genetic effects. Broad-sense heritability varied from zero to 0.699, with a median of 0.125. Significant additive genetic variance was observed for highly heritable metabolites, but dominance variance was not significantly present. As some metabolites are particularly favorable for human nutrition, for instance, future research should address the identification of locus-specific genetic effects and investigate metabolites as the molecular basis of traditional milk performance test traits.

  • 107.
    Zebunke, Manuela
    et al.
    Institute of Behavioural Physiology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Repsilber, Dirk
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden.
    Nuernberg, Gerd
    Institute of Genetics and Biometry, Leibnitz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Wittenburg, Doerte
    Institute of Genetics and Biometry, Leibnitz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Puppe, Birger
    Institute of Behavioural Physiology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany; Behavioural Sciences, Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany.
    The backtest in pigs revisited: an analysis of intra-situational behaviour2015In: Applied Animal Behaviour Science, ISSN 0168-1591, E-ISSN 1872-9045, Vol. 169, p. 17-25Article in journal (Refereed)
    Abstract [en]

    The occurrence of different behavioural phenotypes in animals (regarding temperament and personality) has increasingly attracted the attention of scientists dealing with farm animal breeding, management and welfare. As part of the adaptation repertoire, coping behaviour describes how animals deal with challenging situations. To detect different coping strategies (active vs. passive) in domestic pigs, Hessing et al. (1993) suggested using the backtest at an early age. However, the literature contains ambiguous results and criticism of the backtest. Thus, referring to Jensen (1995), the aim of our study was to analyse the backtest in terms of intra-situational behaviour (frequency distribution, behavioural consistency, heritability) in a large sample of domestic piglets (n = 3555). By using a statistical resampling analysis we wanted to verify whether the individual variation in the behaviour of the piglets in the repeated backtest indicates coping strategies or just random variation. The backtest was repeated four times between the first and fourth week of life (ages 5, 12, 19 and 26 days), and the latency, total duration and frequency of all struggling attempts were recorded. Our results show a continuous, unimodal distribution in the frequency parameter and an apparent bimodal distribution in the latency and duration parameter, that probably represents a unimodal distribution with a 'ceiling-effect'. The intra-test consistency of the behaviour (Spearman rank correlation (r(S)) and repeatability (R)) was moderate (r(S) = 0.19-0.45, p < 0.001; R = 0.25-0.39), indicating at least a certain degree of behavioural consistency. The resampling analysis revealed that the piglets did not show just random variation in behaviour. Moreover, the piglets did not display a general habituation to the repeated backtest. Based on a large pedigree, we calculated that the heritability of the behavioural parameters ranged from 0.17 to 0.43. In conclusion, the repeated backtest does not provide evidence for definitive coping strategies that are clearly separable. We instead found pronounced individual dispositions that are partly determined by genetics along a continuum from active to passive coping behaviour. This means that individuals show both behavioural consistency and flexibility in behaviour.

  • 108. Ziegler, Andreas
    et al.
    Repsilber, Dirk
    Data rotation for efficient comparative genomics2004Conference paper (Refereed)
  • 109.
    Östlund-Lagerström, Lina
    et al.
    Örebro University, School of Medical Sciences.
    Kihlgren, Annica
    Örebro University, School of Health Sciences.
    Repsilber, Dirk
    Örebro University, School of Medical Sciences.
    Björkstén, Bengt
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden.
    Brummer, Robert Jan
    Örebro University, School of Medical Sciences.
    Schoultz, Ida
    Örebro University, School of Medical Sciences.
    Probiotic administration among free-living older adults: a double blinded, randomised, placebo-controlled clinical trialManuscript (preprint) (Other academic)
  • 110.
    Östlund-Lagerström, Lina
    et al.
    Nutrition and Physical Activity Research Centre, Örebro University, Örebro, Sweden; Nutrition Gut Brain Interactions Research Centre, School of Health and Medical Sciences, Faculty of Health and Medicine, Örebro University, Örebro, Sweden.
    Kihlgren, Annica
    Örebro University, School of Health Sciences. Nutrition and Physical Activity Research Centre, Örebro University, Örebro, Sweden.
    Repsilber, Dirk
    Örebro University, School of Medical Sciences.
    Björkstén, Bengt
    Nutrition and Physical Activity Research Centre, Örebro University, Örebro, Sweden; Nutrition Gut Brain Interactions Research Centre, School of Health and Medical Sciences, Faculty of Health and Medicine, Örebro University, Örebro, Sweden; Institute of Environmental Medicine, Karolinska institutet, Stockholm, Sweden.
    Brummer, Robert Jan
    Örebro University, School of Medical Sciences. Nutrition and Physical Activity Research Centre, Örebro University, Örebro, Sweden; Nutrition Gut Brain Interactions Research Centre, Örebro University, Örebro, Sweden.
    Schoultz, Ida
    Örebro University, School of Medical Sciences.
    Probiotic administration among free-living older adults: a double blinded, randomized, placebo-controlled clinical trial2016In: Nutrition Journal, ISSN 1475-2891, E-ISSN 1475-2891, Vol. 15, article id 80Article in journal (Refereed)
    Abstract [en]

    Background: Diseases of the digestive system have been found to contribute to a higher symptom burden in older adults. Thus, therapeutic strategies able to treat gastrointestinal discomfort might impact the overall health status and help older adults to increase their overall health status and optimal functionality.

    Objective: The aim of this double-blinded, randomized, placebo-controlled clinical trial was to evaluate the effect of the probiotic strain Lactobacillus reuteri on digestive health and wellbeing in older adults.

    Methods: The study enrolled general older adults (>65 years). After eligibility screening qualified subjects (n = 290) participated in a 2-arm study design, with each arm consisting of 12 weeks of intervention of either active or placebo product. Primary outcome measure was set to changes in gastrointestinal symptoms and secondary outcome measures were changes in level of wellbeing, anxiety and stress. Follow up was performed at 8 and 12 weeks.

    Results: No persistent significant effects were observed on the primary or secondary outcome parameters of the study. A modest effect was observed in the probiotic arm, were levels of stress decreased at week 8 and 12. Similarly, we found that subjects suffering from indigestion and abdominal pain, respectively, showed a significant decrease of anxiety at week 8 after probiotic treatment, but not at week 12.

    Conclusion: The RCT failed to show any improvement in digestive health after daily intake of a probiotic supplement containing L. reuteri. Neither was any significant improvement in wellbeing, stress or anxiety observed. Even though the RCT had a negative outcome, the study highlights issues important to take into consideration when designing trials among older adults.

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