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  • 1.
    de Mas, Igor Marin
    et al.
    Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain;; Institute of Biomedicine of Universitat de Barcelona (IBUB) and CSIC-Associated Unit, Barcelona, Spain.
    Selivanov, Vitaly A.
    Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain; Institute of Biomedicine of Universitat de Barcelona (IBUB) and CSIC-Associated Unit, Barcelona, Spain; A.N.Belozersky Institute of Physico-Chemical Biology, Moscow, Russia.
    Marin, Silvia
    Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain;; Institute of Biomedicine of Universitat de Barcelona (IBUB) and CSIC-Associated Unit, Barcelona, Spain.
    Roca, Josep
    Hospital Clínic, August Pi i Sunyer Biomedical Research Institute (IDIBAPS),Centro de Investigación Biomédica en Red de Enfermedade Respiratorias (CIBERES) Universitat de Barcelona, Barcelona, Spain.
    Oresic, Matej
    Technical Research Centre of Finland, Espoo, Finland; Institute for Molecular Medicine, Helsinki, Finland.
    Agius, Loranne
    Institute of Cellular Medicine, The Medical School, Newcastle University, Newcastle, UK.
    Cascante, Marta
    Department of Biochemistry and Molecular Biology, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain; Institute of Biomedicine of Universitat de Barcelona (IBUB) and CSIC-Associated Unit, Barcelona, Spain.
    Compartmentation of glycogen metabolism revealed from 13C isotopologue distributions2011In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 5, article id 175Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Stable isotope tracers are used to assess metabolic flux profiles in living cells. The existing methods of measurement average out the isotopic isomer distribution in metabolites throughout the cell, whereas the knowledge of compartmental organization of analyzed pathways is crucial for the evaluation of true fluxes. That is why we accepted a challenge to create a software tool that allows deciphering the compartmentation of metabolites based on the analysis of average isotopic isomer distribution.

    RESULTS: The software Isodyn, which simulates the dynamics of isotopic isomer distribution in central metabolic pathways, was supplemented by algorithms facilitating the transition between various analyzed metabolic schemes, and by the tools for model discrimination. It simulated 13C isotope distributions in glucose, lactate, glutamate and glycogen, measured by mass spectrometry after incubation of hepatocytes in the presence of only labeled glucose or glucose and lactate together (with label either in glucose or lactate). The simulations assumed either a single intracellular hexose phosphate pool, or also channeling of hexose phosphates resulting in a different isotopic composition of glycogen. Model discrimination test was applied to check the consistency of both models with experimental data. Metabolic flux profiles, evaluated with the accepted model that assumes channeling, revealed the range of changes in metabolic fluxes in liver cells.

    CONCLUSIONS: The analysis of compartmentation of metabolic networks based on the measured 13C distribution was included in Isodyn as a routine procedure. The advantage of this implementation is that, being a part of evaluation of metabolic fluxes, it does not require additional experiments to study metabolic compartmentation. The analysis of experimental data revealed that the distribution of measured 13C-labeled glucose metabolites is inconsistent with the idea of perfect mixing of hexose phosphates in cytosol. In contrast, the observed distribution indicates the presence of a separate pool of hexose phosphates that is channeled towards glycogen synthesis.

  • 2.
    Lindfors, Erno
    et al.
    VTT Technical Research Centre of Finland, Espoo, Finland; LifeGlimmer GmbH, Berlin, Germany; Chemistry Building, Wageningen, Netherlands.
    Jouhten, Paula
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Oja, Merja
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Rintala, Eija
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Oresic, Matej
    Örebro University, School of Medical Sciences. VTT Technical Research Centre of Finland, Espoo, Finland.
    Penttilä, Merja
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Integration of transcription and flux data reveals molecular paths associated with differences in oxygen-dependent phenotypes of Saccharomyces cerevisiae2014In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 8, article id 16Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Saccharomyces cerevisiae is able to adapt to a wide range of external oxygen conditions. Previously, oxygen-dependent phenotypes have been studied individually at the transcriptional, metabolite, and flux level. However, the regulation of cell phenotype occurs across the different levels of cell function. Integrative analysis of data from multiple levels of cell function in the context of a network of several known biochemical interaction types could enable identification of active regulatory paths not limited to a single level of cell function.

    RESULTS: The graph theoretical method called Enriched Molecular Path detection (EMPath) was extended to enable integrative utilization of transcription and flux data. The utility of the method was demonstrated by detecting paths associated with phenotype differences of S. cerevisiae under three different conditions of oxygen provision: 20.9%, 2.8% and 0.5%. The detection of molecular paths was performed in an integrated genome-scale metabolic and protein-protein interaction network.

    CONCLUSIONS: The molecular paths associated with the phenotype differences of S. cerevisiae under conditions of different oxygen provisions revealed paths of molecular interactions that could potentially mediate information transfer between processes that respond to the particular oxygen availabilities.

  • 3.
    Neumann, Gunter
    et al.
    School of Medical Health (MV), Örebro University, Örebro, Sweden.
    Wall, Rebecca
    Örebro University, School of Medical Sciences.
    Rangel, Ignacio
    Örebro University, School of Medical Sciences.
    Marques, Tatiana M.
    Örebro University, School of Medical Sciences.
    Repsilber, Dirk
    Örebro University, School of Medical Sciences.
    Qualitative modelling of the interplay of inflammatory status and butyrate in the human gut: a hypotheses about robust bi-stability2018In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 12, no 1, article id 144Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Gut microbiota interacts with the human gut in multiple ways. Microbiota composition is altered in inflamed gut conditions. Likewise, certain microbial fermentation products as well as the lipopolysaccharides of the outer membrane are examples of microbial products with opposing influences on gut epithelium inflammation status. This system of intricate interactions is known to play a core role in human gut inflammatory diseases. Here, we present and analyse a simplified model of bidirectional interaction between the microbiota and the host: in focus is butyrate as an example for a bacterial fermentation product with anti-inflammatory properties.

    RESULTS: We build a dynamical model based on an existing model of inflammatory regulation in gut epithelial cells. Our model introduces both butyrate as a bacterial product which counteracts inflammation, as well as bacterial LPS as a pro-inflammatory bacterial product. Moreover, we propose an extension of this model that also includes a feedback interaction towards bacterial composition. The analysis of these dynamical models shows robust bi-stability driven by butyrate concentrations in the gut. The extended model hints towards a further possible enforcement of the observed bi-stability via alteration of gut bacterial composition. A theoretical perspective on the stability of the described switch-like character is discussed.

    CONCLUSIONS: Interpreting the results of this qualitative model allows formulating hypotheses about the switch-like character of inflammatory regulation in the gut epithelium, involving bacterial products as constitutive parts of the system. We also speculate about possible explanations for observed bimodal distributions in bacterial compositions in the human gut. The switch-like behaviour of the system proved to be mostly independent of parameter choices. Further implications of the qualitative character of our modeling approach for the robustness of the proposed hypotheses are discussed, as well as the pronounced role of butyrate compared to other inflammatory regulators, especially LPS, NF- κB and cytokines.

  • 4.
    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/.

  • 5.
    Yetukuri, Laxman
    et al.
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Katajamaa, Mikko
    Turku Centre for Biotechnology, Turku, Finland.
    Medina-Gomez, Gema
    University of Cambridge Department of Clinical Biochemistry, Addenbrooke's Hospital, Cambridge, UK.
    Seppänen-Laakso, Tuulikki
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Vidal-Puig, Antonio
    University of Cambridge Department of Clinical Biochemistry, Addenbrooke's Hospital, Cambridge, UK.
    Oresic, Matej
    VTT Technical Research Centre of Finland, Espoo, Finland.
    Bioinformatics strategies for lipidomics analysis: characterization of obesity related hepatic steatosis2007In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 1, article id 12Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Lipids are an important and highly diverse class of molecules having structural, energy storage and signaling roles. Modern analytical technologies afford screening of many lipid molecular species in parallel. One of the biggest challenges of lipidomics is elucidation of important pathobiological phenomena from the integration of the large amounts of new data becoming available.

    RESULTS: We present computational and informatics approaches to study lipid molecular profiles in the context of known metabolic pathways and established pathophysiological responses, utilizing information obtained from modern analytical technologies. In order to facilitate identification of lipids, we compute the scaffold of theoretically possible lipids based on known lipid building blocks such as polar head groups and fatty acids. Each compound entry is linked to the available information on lipid pathways and contains the information that can be utilized for its automated identification from high-throughput UPLC/MS-based lipidomics experiments. The utility of our approach is demonstrated by its application to the lipidomic characterization of the fatty liver of the genetically obese insulin resistant ob/ob mouse model. We investigate the changes of correlation structure of the lipidome using multivariate analysis, as well as reconstruct the pathways for specific molecular species of interest using available lipidomic and gene expression data.

    CONCLUSION: The methodology presented herein facilitates identification and interpretation of high-throughput lipidomics data. In the context of the ob/ob mouse liver profiling, we have identified the parallel associations between the elevated triacylglycerol levels and the ceramides, as well as the putative activated ceramide-synthesis pathways.

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