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11	Physical Aspects of Min Oscillations in Escherichia Coli Meacci, Giovanni 25 January 2007 (has links) (PDF) The subject of this thesis is the generation of spatial temporal structures in living cells. Specifically, we studied the Min-system in the bacterium Escherichia coli. It consists of the MinC, the MinD, and the MinE proteins, which play an important role in the correct selection of the cell division site. The Min-proteins oscillate between the two cell poles and thereby prevent division at these locations. In this way, E. coli divides at the center, producing two daughter cells of equal size, providing them with the complete genetic patrimony. Our goal is to perform a quantitative study, both theoretical and experimental, in order to reveal the mechanism underlying the Min-oscillations. Experimentally, we characterize theMin-system, measuring the temporal period of the oscillations as a function of the cell length, the time-averaged protein distributions, and the in vivo Min-protein mobility by means of different fluorescence microscopy techniques. Theoretically, we discuss a deterministic description based on the exchange of Minproteins between the cytoplasm and the cytoplasmic membrane and on the aggregation current induced by the interaction between membrane-bound proteins. Oscillatory solutions appear via a dynamic instability of the homogenous protein distributions. Moreover, we perform stochastic simulations based on a microscopic description, whereby the probability for each event is calculated according to the corresponding probability in the master equation. Starting from this microscopic description, we derive Langevin equations for the fluctuating protein densities which correspond to the deterministic equations in the limit of vanishing noise. Stochastic simulations justify this deterministic model, showing that oscillations are resistant to the perturbations induced by the stochastic reactions and diffusion. Predictions and assumptions of our theoretical model are compatible with our experimental findings. Altogether, these results enable us to propose further experiments in order to quantitatively compare the different models proposed so far and to test our model with even higher precision. They also point to the necessity of performing such an analysis through single cell measurements. Min-Protein-Oscillations biochemical reactions Theory and modeling: computer simulation cell growth and division Fluorescence Correlation Spectroscopy Protein mobility Fluctuation phenomena random process noise self-organaized systems pattern fo Min-Protein-Oszillationen biochemische Reaktionen Zellwachstum und -teilung Spektroskopie Mobilitaet von Proteinen Fluktuationen stochastische Prozesse Rauschen selbstorganisierte Systeme Musterbild ddc:570 rvk:WG 1700 Escherichia Coli Biologische Oszillation Biochemische Reaktion Computersimulation Zellwachstum Zellteilung Musterbildung
12	How Does a Single Cell Know When the Liver Has Reached Its Correct Size? Hohmann, Nadine, Weiwei, Wei, Dahmen, Uta, Dirsch, Olaf, Deutsch, Andreas, Voss-Böhme, Anja 14 July 2014 (has links) (PDF) The liver is a multi-functional organ that regulates major physiological processes and that possesses a remarkable regeneration capacity. After loss of functional liver mass the liver grows back to its original, individual size through hepatocyte proliferation and apoptosis. How does a single hepatocyte ‘know’ when the organ has grown to its final size? This work considers the initial growth phase of liver regeneration after partial hepatectomy in which the mass is restored. There are strong and valid arguments that the trigger of proliferation after partial hepatectomy is mediated through the portal blood flow. It remains unclear, if either or both the concentration of metabolites in the blood or the shear stress are crucial to hepatocyte proliferation and liver size control. A cell-based mathematical model is developed that helps discriminate the effects of these two potential triggers. Analysis of the mathematical model shows that a metabolic load and a hemodynamical hypothesis imply different feedback mechanisms at the cellular scale. The predictions of the developed mathematical model are compared to experimental data in rats. The assumption that hepatocytes are able to buffer the metabolic load leads to a robustness against short-term fluctuations of the trigger which can not be achieved with a purely hemodynamical trigger. Leber Hepatozyten Zellwachstum Proliferation Apoptose partielle Hepatektomie TU Dresden Publikationsfonds liver hepatocyte proliferation apoptosis partial hepatectomy Technical University Dresden Publication funds ddc:500 ddc:610 rvk:TA 1000 rvk:XA 10000
13	How Does a Single Cell Know When the Liver Has Reached Its Correct Size? Hohmann, Nadine, Weiwei, Wei, Dahmen, Uta, Dirsch, Olaf, Deutsch, Andreas, Voss-Böhme, Anja 14 July 2014 (has links) The liver is a multi-functional organ that regulates major physiological processes and that possesses a remarkable regeneration capacity. After loss of functional liver mass the liver grows back to its original, individual size through hepatocyte proliferation and apoptosis. How does a single hepatocyte ‘know’ when the organ has grown to its final size? This work considers the initial growth phase of liver regeneration after partial hepatectomy in which the mass is restored. There are strong and valid arguments that the trigger of proliferation after partial hepatectomy is mediated through the portal blood flow. It remains unclear, if either or both the concentration of metabolites in the blood or the shear stress are crucial to hepatocyte proliferation and liver size control. A cell-based mathematical model is developed that helps discriminate the effects of these two potential triggers. Analysis of the mathematical model shows that a metabolic load and a hemodynamical hypothesis imply different feedback mechanisms at the cellular scale. The predictions of the developed mathematical model are compared to experimental data in rats. The assumption that hepatocytes are able to buffer the metabolic load leads to a robustness against short-term fluctuations of the trigger which can not be achieved with a purely hemodynamical trigger. info:eu-repo/classification/ddc/500 ddc:500 info:eu-repo/classification/ddc/610 ddc:610
14	Physical Aspects of Min Oscillations in Escherichia Coli Meacci, Giovanni 20 December 2006 (has links) The subject of this thesis is the generation of spatial temporal structures in living cells. Specifically, we studied the Min-system in the bacterium Escherichia coli. It consists of the MinC, the MinD, and the MinE proteins, which play an important role in the correct selection of the cell division site. The Min-proteins oscillate between the two cell poles and thereby prevent division at these locations. In this way, E. coli divides at the center, producing two daughter cells of equal size, providing them with the complete genetic patrimony. Our goal is to perform a quantitative study, both theoretical and experimental, in order to reveal the mechanism underlying the Min-oscillations. Experimentally, we characterize theMin-system, measuring the temporal period of the oscillations as a function of the cell length, the time-averaged protein distributions, and the in vivo Min-protein mobility by means of different fluorescence microscopy techniques. Theoretically, we discuss a deterministic description based on the exchange of Minproteins between the cytoplasm and the cytoplasmic membrane and on the aggregation current induced by the interaction between membrane-bound proteins. Oscillatory solutions appear via a dynamic instability of the homogenous protein distributions. Moreover, we perform stochastic simulations based on a microscopic description, whereby the probability for each event is calculated according to the corresponding probability in the master equation. Starting from this microscopic description, we derive Langevin equations for the fluctuating protein densities which correspond to the deterministic equations in the limit of vanishing noise. Stochastic simulations justify this deterministic model, showing that oscillations are resistant to the perturbations induced by the stochastic reactions and diffusion. Predictions and assumptions of our theoretical model are compatible with our experimental findings. Altogether, these results enable us to propose further experiments in order to quantitatively compare the different models proposed so far and to test our model with even higher precision. They also point to the necessity of performing such an analysis through single cell measurements. info:eu-repo/classification/ddc/570 ddc:570

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