Potassium Starvation in Yeast: Mechanisms of Homeostasis Revealed by Mathematical Modeling

The intrinsic ability of cells to adapt to a wide range of environmental conditions is a fundamental process required for survival. Potassium is the most abundant cation in living cells and is required for essential cellular processes, including the regulation of cell volume, pH and protein synthesis. Yeast cells can grow from low micromolar to molar potassium concentrations and utilize sophisticated control mechanisms to keep the internal potassium concentration in a viable range. We developed a mathematical model for Saccharomyces cerevisiae to explore the complex interplay between biophysical forces and molecular regulation facilitating potassium homeostasis. By using a novel inference method (“the reverse tracking algorithm”) we predicted and then verified experimentally that the main regulators under conditions of potassium starvation are proton fluxes responding to changes of potassium concentrations. In contrast to the prevailing view, we show that regulation of the main potassium transport systems (Trk1,2 and Nha1) in the plasma membrane is not sufficient to achieve homeostasis

Membranes with the Same Ion Channel Populations but Different Excitabilities

Electrical signaling allows communication within and between different tissues and is necessary for the survival of multicellular organisms. The ionic transport that underlies transmembrane currents in cells is mediated by transporters and channels. Fast ionic transport through channels is typically modeled with a conductance-based formulation that describes current in terms of electrical drift without diffusion. In contrast, currents written in terms of drift and diffusion are not as widely used in the literature in spite of being more realistic and capable of displaying experimentally observable phenomena that conductance-based models cannot reproduce (e.g. rectification). The two formulations are mathematically related: conductance-based currents are linear approximations of drift-diffusion currents. However, conductance-based models of membrane potential are not first-order approximations of drift-diffusion models. Bifurcation analysis and numerical simulations show that the two approaches predict qualitatively and quantitatively different behaviors in the dynamics of membrane potential. For instance, two neuronal membrane models with identical populations of ion channels, one written with conductance-based currents, the other with drift-diffusion currents, undergo transitions into and out of repetitive oscillations through different mechanisms and for different levels of stimulation. These differences in excitability are observed in response to excitatory synaptic input, and across different levels of ion channel expression. In general, the electrophysiological profiles of membranes modeled with drift-diffusion and conductance-based models having identical ion channel populations are different, potentially causing the input-output and computational properties of networks constructed with these models to be different as well. The drift-diffusion formulation is thus proposed as a theoretical improvement over conductance-based models that may lead to more accurate predictions and interpretations of experimental data at the single cell and network levels

Fuel Saving in Coastal Areas: A Case Study of the Oslo Fjord

Fossil fuels such as marine diesel oil (MDO) account for a significant part of the shipping industry’s total operating costs and have a certain negative impact on the environment. Maritime transport emits around 1000 million tonnes of CO2 annually and is responsible for about 2.5% of global greenhouse gas emissions. To focus on fuel saving is therefore important for both economic and environmental reasons. It is indicative that ship owners are now using weather routeing to save fuel and reduce emissions, particularly on long passages. In coastal areas, navigation is limited by traffic rules. This study examines whether fuel consumption can be reduced with current routeing in confined coastal areas, in this case a relatively short voyage in the Oslo Fjord, Norway. An advanced bridge simulator is used, where different current fields from a high-resolution ocean model are implemented. The results reveal that if the voyage is conducted on a typical field with following currents, instead of a typical counter current field, the travel time will be reduced by 12% for a typical vessel with speed through water set to 16.7 knots. On following currents, the vessel speed can be reduced to 15.7 knots and the voyage is completed within the same time as if no currents are present. This implies approximately a 15% reduction in fuel consumption for the vessel tested. The results also reveal that fuel consumption can be reduced if the vessel is operated within most favourable or least unfavourable currents inside the main traffic lanes