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Joachim W. Deitmer, FB Biologie mit FB Mathematik und ITWM

Joachim W. Deitmer, FB Biologie mit FB Mathematik und ITWM. Die Rolle der Neuroglia bei der Bildung, Funktion und Plastizität von Synapsen. Räumlich-zeitliche Interaktionen zelluläre Signalmoleküle.

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Joachim W. Deitmer, FB Biologie mit FB Mathematik und ITWM

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  1. Joachim W. Deitmer, FB Biologiemit FB Mathematik und ITWM Die Rolle der Neuroglia bei der Bildung, Funktion und Plastizität von Synapsen Räumlich-zeitliche Interaktionen zelluläre Signalmoleküle

  2. A model reduction approach to the kineticsof the monocarboxylate transporterMCT1 and carbonic anhydrase II MCT MCT 1 H+ 1 Lac- Joachim Almquist1, Henning Schmidt1, Patrick Lang2, Dieter Prätzel-Wolters2, Joachim W. Deitmer3, Mats Jirstrand1, and Holger Becker3 1Fraunhofer-Chalmers Centre, Gothenburg, Sweden 2Institut für Techno- und Wirtschaftsmathematik (ITWM) Fraunhofer Gesellschaft, Kaiserslautern, Germany 3Technische Universität Kaiserslautern, Kaiserslautern, Germany Neuron-glia interactions

  3. Aim of this Project To determine the mechanism of the monocarboxylate transporter (MCT1) and to present a mechanistic hypothesis of how MCT1 interacts with the enzyme carbonic anhydrase II (CAII). The modelling process might provide ideas for this. To derive a rate expression for the MCT1 that also includes the effect of CAII. This could be used in other models. Protein expression in Xenopus oocytes Injection of rat MCT1-cRNA Injection of CAII (isolated from bovine erythrocytes) Microelectrodes for intrcellular pH measurements ODE modelling Model reduction Methods - Electrophysiological Techniques and Mathematical Modeling

  4. Functionally expressed proteins in Xenopus oocytes: Interactions with carboanhydrases? • Messung von Membranströmen in ‚Voltage-Clamp‘ • Messung von cytosolischem pH und Na+ mit ionen- selektiven Mikroelektroden • Struktur-Funktion-Analyse durch gezielte Mutationen Funktionelle heterologe Expression von Membrantransportproteinen in Frosch-Oozyten (Xenopus laevis) Carboanhydrase II Modell der Wechselwirkung zwischen Carboanhydrase und Membrantransporter (NBCe1=Natrium-Bikarbonat-Kotransporter NBCe1 und Carboanhydrase ko-exprimiert

  5. The Model Monocarboxylate transporter MCT 1 H+ 1 Lac- Ordinary differential equation model of the transporter states shown in the cartoon

  6. CAII Included in Model The effect of CAII is included in the model as an increased rate of proton uptake and release on the intracellular side of the transporter.

  7. Comparing Measurements with Simulations Efflux experiments with and without CAII (A,B) are compared with the model (C). Influx experiments with and without CAII (A,C) are compared with the model (B,D).

  8. Kooperationen • Prof. D. Prätzel-Wolters, FB Mathematik und ITWM • ITWM: Dr. P. Lang • Fraunhofer-Chalmers-Centre, Göteborg, Schweden: Prof. M. Jirstrand, J. Almquist Erfolge/Fortschritte: Erstes Paper über das Modell in Revision Bisher dem Projekt zugewiesene Mittel: 30 T€ für 2008

  9. Weiterer Fahrplan • Erweiterung des Modells mit Voraussagen (Einbeziehung von verschiedenen Isoformen und Mutanten der Carboanhydrase sowie mit NBCe1 • Experimentelle Überprüfung dieser Voraussagen und Simulierung weiterer Parameter • Neues Projekt (DFG-Antrag wird gerade geschrieben): Mechanismen und Modellierung der Protonen-Pufferung in Zellen

  10. Future Projects • Measuring, analyzing and modelling of the capacity and dynamics of cellular H+ buffering - Spatial dynamics of buffering within a cell and role of carbonic anhydrases - The role of acid/base-coupled membrane transporters, such as the NBC, for buffering

  11. Thank you! Gilt das nur für den Betze?

  12. Measurement of buffer capacity CA CO2 +H2O H+ + HCO3- Henderson- Hasselbalch equation:pH = pK‘ log [HCO3-]/[CO2] [HCO3-]i = 10(pHi-pK‘)x [CO2] (pK‘=6.1) Buffer capacity = acid/base injection / dpHi βt = intrinsic + CO2/HCO3—dependent ßCO2 ≈ 2.3 [HCO3-] dpHi By measuring pHi, ß can be determined! Addition/injection of acid

  13. Model Reduction One possible set of constraints that can be used to reduce the ODE-system. Solving this set of equations yields a explicit rate expression for the cross-membrane transport of MCT1 substrates,T.

  14. Substrate Inhibition Predictions Model reduction with different assumptions on transporter properties leads to predictions of inhibition by single substrate presence.

  15. A Hypothesis for the MCT1-CAII-mechanism A hypothesis for the MCT1-CAII-mechanism. One or several CAII molecules close to the inner mouth of MCT1 might be working as a proton antenna. If proton uptake and release are the rate-limiting steps of transport, MCT1 turnover could be increase by this antenna.

  16. Voltage dependence of the total buffer capacity (ßT) of oocytes expressing NBC Becker & Deitmer (2004) J. Biol. Chem.279, 28057-28062

  17. Aim of these studies • Measuring and modelling (simulating) H+ buffer capacity • Predicting parameters of cellular buffering • Testing predicted parameters in experiment • What consequences do our findings might have for pH-dependent processes in systems (cells, tissue, organs)?

  18. Data from Substrate Inhibition The inhibition predictions are tested in experiments.

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