Showing papers by "Stefan Hohmann published in 2015"

An integrated view on a eukaryotic osmoregulation system

Abstract: Osmoregulation encompasses active homeostatic processes that ensure proper cell volume, shape and turgor as well as an intercellular milieu optimal for the diverse biochemical processes. Recent studies demonstrate that yeast cells operate within a tight window of cellular water concentrations that still allows rapid diffusion of biomolecules while already moderate cell compression following hyper-osmotic stress leads to macromolecular crowding and a slow-down of cellular processes. Yeast cells accumulate glycerol as compatible osmolyte under hyper-osmotic stress to regain cell volume and turgor and release glycerol following a hypo-osmotic shock. The high osmolarity glycerol (HOG) response pathway controls glycerol accumulation at various levels, where each mechanism contributes to the temporal and quantitative pattern of volume recovery: inhibition of glycerol efflux, direct activation of the first enzyme in glycerol biosynthesis, stimulation of glycolytic flux as well as upregulation of expression of genes encoding enzymes in glycerol biosynthesis and an active glycerol uptake system. The HOG mitogen-activated protein kinase (MAPK) pathway communicates with the other yeast MAPK pathways to control cell morphogenesis. Cross-talk between the MAPK pathways has recently been used to re-wire osmostress-controlled expression of glycerol biosynthesis genes from Hog1 to Kss1-Fus3. The results of this study further illustrate the key importance of glycerol accumulation under osmostress and allow studying Hog1-dependent and independent processes as well as redundancy and robustness of the MAPK system.

Molecular communication: crosstalk between the Snf1 and other signaling pathways

Abstract: The yeast Saccharomyces cerevisiae employs different conserved signaling pathways to adapt to altered availability of nutrient and energy sources. Crosstalk between the pathways occurs to integrate different internal and external stimuli and adjust cellular metabolism, growth and proliferation to altered environmental conditions. The main glucose repression pathway, Snf1/Mig1, plays an essential role in adaptation to glucose limitation. However, the Snf1 protein kinase is also involved in regulation of many other cellular processes. We summarize evidence that Snf1 is part of a network of communicating pathways, and we suggest research directions that may help elucidating signal flow within this network.

Rewiring yeast osmostress signalling through the MAPK network reveals essential and non-essential roles of Hog1 in osmoadaptation

Abstract: Mitogen-activated protein kinases (MAPKs) have a number of targets which they regulate at transcriptional and post-translational levels to mediate specific responses. The yeast Hog1 MAPK is essential for cell survival under hyperosmotic conditions and it plays multiple roles in gene expression, metabolic regulation, signal fidelity and cell cycle regulation. Here we describe essential and non-essential roles of Hog1 using engineered yeast cells in which osmoadaptation was reconstituted in a Hog1-independent manner. We rewired Hog1-dependent osmotic stress-induced gene expression under the control of Fus3/Kss1 MAPKs, which are activated upon osmostress via crosstalk in hog1Δ cells. This approach revealed that osmotic up-regulation of only two Hog1-dependent glycerol biosynthesis genes, GPD1 and GPP2, is sufficient for successful osmoadaptation. Moreover, some of the previously described Hog1-dependent mechanisms appeared to be dispensable for osmoadaptation in the engineered cells. These results suggest that the number of essential MAPK functions may be significantly smaller than anticipated and that knockout approaches may lead to over-interpretation of phenotypic data.

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

Abstract: The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability.

Network reconstruction and validation of the Snf1/AMPK pathway in baker’s yeast based on a comprehensive literature review

Abstract: The SNF1/AMPK protein kinase has a central role in energy homeostasis in eukaryotic cells. It is activated by energy depletion and stimulates processes leading to the production of ATP while it downregulates ATP-consuming processes. The yeast SNF1 complex is best known for its role in glucose derepression. We performed a network reconstruction of the Snf1 pathway based on a comprehensive literature review. The network was formalised in the rxncon language, and we used the rxncon toolbox for model validation and gap filling. We present a machine-readable network definition that summarises the mechanistic knowledge of the Snf1 pathway. Furthermore, we used the known input/output relationships in the network to identify and fill gaps in the information transfer through the pathway, to produce a functional network model. Finally, we convert the functional network model into a rule-based model as a proof-of-principle. The workflow presented here enables large scale reconstruction, validation and gap filling of signal transduction networks. It is analogous to but distinct from that established for metabolic networks. We demonstrate the workflow capabilities, and the direct link between the reconstruction and dynamic modelling, with the Snf1 network. This network is a distillation of the knowledge from all previous publications on the Snf1/AMPK pathway. The network is a knowledge resource for modellers and experimentalists alike, and a template for similar efforts in higher eukaryotes. Finally, we envisage the workflow as an instrumental tool for reconstruction of large signalling networks across Eukaryota. A network model in yeast provides a resource for biologists to better understand cellular energy usage. A team led by Marcus Krantz from the Humboldt University of Berlin, Germany, surveyed the scientific literature for mechanistic details about the signaling networks associated with the SNF1 pathway in yeast. This pathway helps maintain proper energy balance in all eukaryotes, including mammals and plants. In yeast, it is primarily used during times of glucose limitation to help cells grow on alternate energy sources. Krantz and colleagues plugged all the published information about the genes, metabolic enzymes and nutrient-responsive cellular processes linked to SNF1 in yeast into their computer network. Scientists can now use this tool for large-scale reconstruction of signaling networks. The resource also provides a template for similar efforts with other pathways or in other organisms.

A fungicide-responsive kinase as a tool for synthetic cell fate regulation

Abstract: Engineered biological systems that precisely execute defined tasks have major potential for medicine and biotechnology. For instance, gene- or cell-based therapies targeting pathogenic cells may replace time- and resource-intensive drug development. Engineering signal transduction systems is a promising, yet presently underexplored approach. Here, we exploit a fungicide-responsive heterologous histidine kinase for pathway engineering and synthetic cell fate regulation in the budding yeast Saccharomyces cerevisiae. Rewiring the osmoregulatory Hog1 MAPK signalling system generates yeast cells programmed to execute three different tasks. First, a synthetic negative feedback loop implemented by employing the fungicide-responsive kinase and a fungicide-resistant derivative reshapes the Hog1 activation profile, demonstrating how signalling dynamics can be engineered. Second, combinatorial integration of different genetic parts including the histidine kinases, a pathway activator and chemically regulated promoters enables control of yeast growth and/or gene expression in a two-input Boolean logic manner. Finally, we implemented a genetic ‘suicide attack’ system, in which engineered cells eliminate target cells and themselves in a specific and controllable manner. Taken together, fungicide-responsive kinases can be applied in different constellations to engineer signalling behaviour. Sensitizing engineered cells to existing chemicals may be generally useful for future medical and biotechnological applications.