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Schaber2012 - Hog pathway in yeast

ABSTRACT: Schaber2012 - Hog pathway in yeast The high osmolarity glycerol (HOG) pathway in the yeast Saccharomyces cerevisiae is one of the best-studied mitogen-activated protein kinase (MAPK) pathways and serves as a prototype signalling system for eukaryotes. This pathway is necessary and sufficient to adapt to high external osmolarity. A key component of this pathway is the stress-activated protein kinase (SAPK) Hog1, which is rapidly phosphorylated by the SAPK kinase Pbs2 upon hyper-osmotic shock, and which is the terminal kinase of two parallel signalling pathways, subsequently called the Sho1 branch and the Sln1 branch, respectively. Ensemble modelling (192 models) is used to study the yeast HOG pathway, a prototype for eukaryotic mitogen-activated kinase signalling systems. The best fit model (Model Nr.22: described here) provides new insights into the function of this system, some of which are then experimentally validated. This model is described in the article: Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast. Schaber J, Baltanas R, Bush A, Klipp E, Colman-Lerner A. Mol Syst Biol. 2012 Nov 13;8:622. Abstract: The high osmolarity glycerol (HOG) pathway in yeast serves as a prototype signalling system for eukaryotes. We used an unprecedented amount of data to parameterise 192 models capturing different hypotheses about molecular mechanisms underlying osmo-adaptation and selected a best approximating model. This model implied novel mechanisms regulating osmo-adaptation in yeast. The model suggested that (i) the main mechanism for osmo-adaptation is a fast and transient non-transcriptional Hog1-mediated activation of glycerol production, (ii) the transcriptional response serves to maintain an increased steady-state glycerol production with low steady-state Hog1 activity, and (iii) fast negative feedbacks of activated Hog1 on upstream signalling branches serves to stabilise adaptation response. The best approximating model also indicated that homoeostatic adaptive systems with two parallel redundant signalling branches show a more robust and faster response than single-branch systems. We corroborated this notion to a large extent by dedicated measurements of volume recovery in single cells. Our study also demonstrates that systematically testing a model ensemble against data has the potential to achieve a better and unbiased understanding of molecular mechanisms. This model is hosted on BioModels Database and identified by: MODEL1209110001 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Joerg Schaber

PROVIDER: BIOMD0000000429 | BioModels | 2012-11-22

REPOSITORIES: BioModels

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Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast.

Schaber Jörg J Baltanas Rodrigo R Bush Alan A Klipp Edda E Colman-Lerner Alejandro A

Molecular systems biology 20120101

The high osmolarity glycerol (HOG) pathway in yeast serves as a prototype signalling system for eukaryotes. We used an unprecedented amount of data to parameterise 192 models capturing different hypotheses about molecular mechanisms underlying osmo-adaptation and selected a best approximating model. This model implied novel mechanisms regulating osmo-adaptation in yeast. The model suggested that (i) the main mechanism for osmo-adaptation is a fast and transient non-transcriptional Hog1-mediated ...[more]

PMID: 23149687

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Project description:This a model from the article: A modelling approach to quantify dynamic crosstalk between the pheromone and the starvation pathway in baker's yeast. Schaber J, Kofahl B, Kowald A, Klipp E FEBS J.2006 Aug; 273(15):3520-33 16884493, Abstract: Cells must be able to process multiple information in parallel and, moreover, they must also be able to combine this information in order to trigger the appropriate response. This is achieved by wiring signalling pathways such that they can interact with each other, a phenomenon often called crosstalk. In this study, we employ mathematical modelling techniques to analyse dynamic mechanisms and measures of crosstalk. We present a dynamic mathematical model that compiles current knowledge about the wiring of the pheromone pathway and the filamentous growth pathway in yeast. We consider the main dynamic features and the interconnections between the two pathways in order to study dynamic crosstalk between these two pathways in haploid cells. We introduce two new measures of dynamic crosstalk, the intrinsic specificity and the extrinsic specificity. These two measures incorporate the combined signal of several stimuli being present simultaneously and seem to be more stable than previous measures. When both pathways are responsive and stimulated, the model predicts that (a) the filamentous growth pathway amplifies the response of the pheromone pathway, and (b) the pheromone pathway inhibits the response of filamentous growth pathway in terms of mitogen activated protein kinase activity and transcriptional activity, respectively. Among several mechanisms we identified leakage of activated Ste11 as the most influential source of crosstalk. Moreover, we propose new experiments and predict their outcomes in order to test hypotheses about the mechanisms of crosstalk between the two pathways. Studying signals that are transmitted in parallel gives us new insights about how pathways and signals interact in a dynamical way, e.g., whether they amplify, inhibit, delay or accelerate each other. This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.

Project description:Petelenz-kurdzeil2013 - Osmo adaptation gpd1D This model is described in the article: Quantitative analysis of glycerol accumulation, glycolysis and growth under hyper osmotic stress. Petelenz-Kurdziel E, Kuehn C, Nordlander B, Klein D, Hong KK, Jacobson T, Dahl P, Schaber J, Nielsen J, Hohmann S, Klipp E. PLoS Comput. Biol. 2013; 9(6): e1003084 Abstract: We provide an integrated dynamic view on a eukaryotic osmolyte system, linking signaling with regulation of gene expression, metabolic control and growth. Adaptation to osmotic changes enables cells to adjust cellular activity and turgor pressure to an altered environment. The yeast Saccharomyces cerevisiae adapts to hyperosmotic stress by activating the HOG signaling cascade, which controls glycerol accumulation. The Hog1 kinase stimulates transcription of genes encoding enzymes required for glycerol production (Gpd1, Gpp2) and glycerol import (Stl1) and activates a regulatory enzyme in glycolysis (Pfk26/27). In addition, glycerol outflow is prevented by closure of the Fps1 glycerol facilitator. In order to better understand the contributions to glycerol accumulation of these different mechanisms and how redox and energy metabolism as well as biomass production are maintained under such conditions we collected an extensive dataset. Over a period of 180 min after hyperosmotic shock we monitored in wild type and different mutant cells the concentrations of key metabolites and proteins relevant for osmoadaptation. The dataset was used to parameterize an ODE model that reproduces the generated data very well. A detailed computational analysis using time-dependent response coefficients showed that Pfk26/27 contributes to rerouting glycolytic flux towards lower glycolysis. The transient growth arrest following hyperosmotic shock further adds to redirecting almost all glycolytic flux from biomass towards glycerol production. Osmoadaptation is robust to loss of individual adaptation pathways because of the existence and upregulation of alternative routes of glycerol accumulation. For instance, the Stl1 glycerol importer contributes to glycerol accumulation in a mutant with diminished glycerol production capacity. In addition, our observations suggest a role for trehalose accumulation in osmoadaptation and that Hog1 probably directly contributes to the regulation of the Fps1 glycerol facilitator. Taken together, we elucidated how different metabolic adaptation mechanisms cooperate and provide hypotheses for further experimental studies. This model is hosted on BioModels Database and identified by: BIOMD0000000610. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Talemi2016 - Yeast osmo-homoestasis This model is described in the article: Systems Level Analysis of the Yeast Osmo-Stat. Talemi SR, Tiger CF, Andersson M, Babazadeh R, Welkenhuysen N, Klipp E, Hohmann S, Schaber J. Sci Rep 2016; 6: 30950 Abstract: Adaptation is an important property of living organisms enabling them to cope with environmental stress and maintaining homeostasis. Adaptation is mediated by signaling pathways responding to different stimuli. Those signaling pathways might communicate in order to orchestrate the cellular response to multiple simultaneous stimuli, a phenomenon called crosstalk. Here, we investigate possible mechanisms of crosstalk between the High Osmolarity Glycerol (HOG) and the Cell Wall Integrity (CWI) pathways in yeast, which mediate adaptation to hyper- and hypo-osmotic challenges, respectively. We combine ensemble modeling with experimental investigations to test in quantitative terms different hypotheses about the crosstalk of the HOG and the CWI pathways. Our analyses indicate that for the conditions studied i) the CWI pathway activation employs an adaptive mechanism with a variable volume-dependent threshold, in contrast to the HOG pathway, whose activation relies on a fixed volume-dependent threshold, ii) there is no or little direct crosstalk between the HOG and CWI pathways, and iii) its mainly the HOG alone mediating adaptation of cellular osmotic pressure for both hyper- as well as hypo-osmotic stress. Thus, by iteratively combining mathematical modeling with experimentation we achieved a better understanding of regulatory mechanisms of yeast osmo-homeostasis and formulated new hypotheses about osmo-sensing. This model is hosted on BioModels Database and identified by: MODEL1606100000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Transcriptome analyses using a wild-type strain of Saccharomyces cerevisiae were performed to assess the overall pattern of gene expression during the transition from glucose-based fermentative to glycerol-based respiratory growth. These experiments revealed a complex suite of metabolic and structural changes associated with the adaptation process. Alterations in gene expression leading to remodeling of various membrane transport systems and the cortical actin cytoskeleton were observed. Transition to respiratory growth was accompanied by alterations in transcript patterns demonstrating not only a general stress response, as seen in earlier studies, but also the oxidative and osmotic stress responses. In some contrast to earlier studies, these experiments identified modulation of expression for many genes specifying transcription factors during the transition to glycerol-based growth. Importantly and unexpectedly, an ordered series of changes was seen in transcript levels from genes encoding components of the TFIID, SAGA (Spt-Ada-Gcn5-Acetyltransferase), and SLIK (Saga LIKe) complexes and all three RNA polymerases, suggesting a modulation of structure for the basal transcriptional machinery during adaptation to respiratory growth. In concert with data given in earlier studies, the results presented here highlight important aspects of metabolic and other adaptations to respiratory growth in yeast that are common to utilization of multiple carbon sources. Importantly, they also identify aspects specific to adaptation of this organism to growth on glycerol as sole carbon source. A time-series illustrating the transition from fermentation using glucose (dextrose) as sole carbon source to respiration using glycerol as sole carbon source. Time points of 15 minutes, 30 minutes and 60 minutes as well as growth on dextrose, glycerol or ethanol as sole carbon source from a starter culture. Three biological replicates of the 30 minute time point and growth on glycerol from starter culture.

Project description:The yeast Saccharomyces cerevisiae is a model for biology and is also one of the most important microorganisms for food and drink production. Surprisingly, only a few genes involved in the adaptation to anthropic niches have been described until now. Wine fermentation and flor aging, which are performed by strains from two closely related groups of yeast, are two technologies that have opposite approaches toward oxygen, which results in contrasting lifestyles for yeast: fermentation growth on grape for wine yeast, and biofilm aerobic growth on ethanol and glycerol contained in wine for flor strains. This pair of environments and the associated yeast populations can be a model for studying adaptation to anthropic environments. In this project, we have obtained high-quality genome sequences of 20 yeast strains from 9 flor yeast, 9 wine yeast as well as EC1118 and haploid derivative 59A. Phylogeny and population structure analysis, based on GATK genotyping, enable us to characterize a group of flor yeast that is clearly different from wine yeast. A comparison of the genomes of wine and flor yeasts using various methods (PCA, nucleotidic diversity, McDonald Kreitman test, potentially impacted genes according to SIFT) enabled us to note divergent regions, or genes, with potential non-neutral evolution, and highly variant genes. The results of these genomic comparisons are echoed by the comparison of a wine and a flor yeast transcriptome. These methods, as expected, highlight key genes that are involved in FLO11 regulation as well as in biofilm growth, but they also revealed the presence of many allelic variations in genes that are involved in the sensing and regulation of osmotic pressure (such as SLN1, HKR1, SSK22, AQY2) and specific metabolic traits, such as the fructophily of flor yeast, which carry a fructophile allele of HXT3. More remarkable is the accumulation of mutations in multiple genes, which creates a pattern of convergent mutations in regulatory networks, as seen in FLO11 regulation or the HOG MAP kinase pathway. The rewiring of these regulatory networks is clearly one of the hallmarks of domestication for the flor yeast genome. Data presented here correspond to the comparison of Flor yeast P3-D5 and wine yeast K1-280-2B transcriptomes under conditions potentially enabling the production of a biofilm.

Dataset Information

Schaber2012 - Hog pathway in yeast

Publications

Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast.

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