Analysis of individual forces.

<p>Separation of <i>J</i>_K into a K⁺ (green) and a H⁺ (blue) dependent part for simulations with parameter sets a) P2a and b) P2b. c) Separation of <i>J</i>_K into a chemical (green) and an electrical (blue) potential dependent part with parameter set P2a. d) Ratio of the electrical and the chemical potential dependent part of <i>J</i>_K with P2a. Simulation of the membrane potential with parameter sets e) P2a and f) P2b.</p

Initial concentrations, global quantities and volumes, and estimated parameters for P1.

<p>Estimated model parameters for stress with 4 different concentrations of KCl. All other <i>L</i>s could be set to 0 without affecting the goodness of fit.</p

Impact of Acute Metal Stress in <i>Saccharomyces cerevisiae</i>

<div><p>Although considered as essential cofactors for a variety of enzymatic reactions and for important structural and functional roles in cell metabolism, metals at high concentrations are potent toxic pollutants and pose complex biochemical problems for cells. We report results of single dose acute toxicity testing in the model organism <i>S. cerevisiae</i>. The effects of moderate toxic concentrations of 10 different human health relevant metals, Ag⁺, Al³⁺, As³⁺, Cd²⁺, Co²⁺, Hg²⁺, Mn²⁺, Ni²⁺, V³⁺, and Zn²⁺, following short-term exposure were analyzed by transcription profiling to provide the identification of early-on target genes or pathways. In contrast to common acute toxicity tests where defined endpoints are monitored we focused on the entire genomic response. We provide evidence that the induction of central elements of the oxidative stress response by the majority of investigated metals is the basic detoxification process against short-term metal exposure. General detoxification mechanisms also comprised the induction of genes coding for chaperones and those for chelation of metal ions via siderophores and amino acids. Hierarchical clustering, transcription factor analyses, and gene ontology data further revealed activation of genes involved in metal-specific protein catabolism along with repression of growth-related processes such as protein synthesis. Metal ion group specific differences in the expression responses with shared transcriptional regulators for both, up-regulation and repression were also observed. Additionally, some processes unique for individual metals were evident as well. In view of current concerns regarding environmental pollution our results may support ongoing attempts to develop methods to monitor potentially hazardous areas or liquids and to establish standardized tests using suitable eukaryotic a model organism.</p></div

A Thermodynamic Model of Monovalent Cation Homeostasis in the Yeast <i>Saccharomyces cerevisiae</i>

<div><p>Cationic and heavy metal toxicity is involved in a substantial number of diseases in mammals and crop plants. Therefore, the understanding of tightly regulated transporter activities, as well as conceiving the interplay of regulatory mechanisms, is of substantial interest. A generalized thermodynamic description is developed for the complex interplay of the plasma membrane ion transporters, membrane potential and the consumption of energy for maintaining and restoring specific intracellular cation concentrations. This concept is applied to the homeostasis of cation concentrations in the yeast cells of <i>S</i>. <i>cerevisiae</i>. The thermodynamic approach allows to model passive ion fluxes driven by the electrochemical potential differences, but also primary or secondary active transport processes driven by the inter- play of different ions (symport, antiport) or by ATP consumption (ATPases). The model—confronted with experimental data—reproduces the experimentally observed potassium and proton fluxes induced by the external stimuli KCl and glucose. The estimated phenomenological constants combine kinetic parameters and transport coefficients. These are in good agreement with the biological understanding of the transporters thus providing a better understanding of the control exerted by the coupled fluxes. The model predicts the flux of additional ion species, like e.g. chloride, as a potential candidate for counterbalancing positive charges. Furthermore, the effect of a second KCl stimulus is simulated, predicting a reduced cellular response for cells that were first exposed to a high KCl stimulus compared to cells pretreated with a mild KCl stimulus. By describing the generalized forces that are responsible for a given flow, the model provides information and suggestions for new experiments. Furthermore, it can be extended to other systems such as e.g. <i>Candida albicans</i>, or selected plant cells.</p></div

Transcriptional metal defense responses of <i>S. cerevisiae</i> to acute metal stress.

<p>Two-dimensional hierarchical cluster heat map of the transcriptional profile of genes responding to at least 2 metal stress conditions and being associated to significant GO-Terms; the displayed intensities are the log2 ratios. Differences with expression levels greater than the mean are colored in red and those below the mean are colored in blue. The histogram summarizes the distribution of the fold-changes of all combinations (47 genes and 10 conditions).</p

Sketch of the system and the model-relevant key elements.

<p>Sketch of the system and the model-relevant key elements.</p

Schematic model of detoxification responses under acute metal stress.

<p>Activation of the antioxidative redox system (AORS) to reduce reactive oxygen species (ROS); Chelation of metal ions (Me) via glutathione (GSH) and metallothionein (MT), sequestration of chelates into the vacuole, storage of metal ions and degradation of proteins, respectively; Extracellular chelation of metals via siderophores (SP) to restrict metal influx; Chelation of metals via histidine (His); Vacuolar and non-vacuolar degradation of metal/protein complexes; Activation of chaperones (CP) for protein folding and degradation of metal/protein complexes.</p

Assignment of phenomenological coefficients to their realizing transporters.

<p>Assignment of phenomenological coefficients to their realizing transporters.</p

Total number of differentially expressed genes.

<p>Descriptive summary of the total number of genes differentially expressed by a factor greater 50% (yellow) or minor 50% (blue) upon treatment with indicated concentrations of metal ions compared to the untreated control; total numbers of up- and down-regulated genes upon the distinct metal stress conditions are indicated in the figure. In total 740 genes were up-regulated, and 283 genes were down-regulated. Detailed information is provided in TS 1, 2, and 3 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0083330#pone.0083330.s002" target="_blank">File S2</a>.</p

Uniquely expressed genes under different metal stress conditions.

<p>Numbers of up- or down-regulated genes under the distinct metal ions; percentage referred to the total numbers of differentially ex- or repressed genes provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0083330#pone-0083330-t003" target="_blank">table 3</a>. Detailed information is given in TS 6 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0083330#pone.0083330.s002" target="_blank">File S2</a>.</p