Dataset Information

Zou2007_MAPK_SignalingNetworks

ABSTRACT: This a model from the article: Modeling specificity in the yeast MAPK signaling networks Zou X, Peng T, Pan Z J. Theor. Biol. (2008);250(1):139-55 17977559 , Abstract: Cells sense several kinds of stimuli and trigger corresponding responses through signaling pathways. As a result, cells must process and integrate multiple signals in parallel to maintain specificity and avoid erroneous cross-talk. In this study, we focus our theoretical effort on understanding specificity of a model network system in yeast, Saccharomyces cerevisiae, which contains three mitogen-activated protein kinase (MAPK) signal transduction cascades that share multiple signaling components. The cellular response to the pheromone, the filamentous growth and osmotic pressure stimuli in yeast is described and an integrative mathematical model for the three MAPK cascades is developed using available literature and experimental data. The theoretical framework for analyzing the specificity of signaling networks [Bardwell, L., Zou, X.F., Nie, Q., Komarova, N.L., 2007. Mathematical models of specificity in cell signaling. Biophys. J. 92, 3425-3441] is extended to include multiple interacting pathways with shared components. Simulations are also performed with any one stimulus, with any two simultaneous stimuli, and with the simultaneous application of the three stimuli. The interactions between the three pathways are systematically investigated. Moreover, the specificity and fidelity of this model system are calculated using our newly developed concept under different stimuli or with specific mutants. Our simulated and calculated results demonstrate that the yeast MAPK signaling network can achieve specificity and fidelity by filtering out spurious cross-talk between the relevant pathways through different mechanisms, such as scaffolding, cross-inhibiting, and feedback control. Proof that Pbs2 and Hog1 are essential for the maintenance of signaling specificity is presented. Our studies provide novel insights into integration of relevant signaling pathways in a biological system and the mechanisms conferring specificity in cellular signaling networks. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. 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. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Harish Dharuri

PROVIDER: MODEL7519354389 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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Publications

Modeling specificity in the yeast MAPK signaling networks.

Zou Xiufen X Peng Tao T Pan Zishu Z

Journal of theoretical biology 20070925 1

Cells sense several kinds of stimuli and trigger corresponding responses through signaling pathways. As a result, cells must process and integrate multiple signals in parallel to maintain specificity and avoid erroneous cross-talk. In this study, we focus our theoretical effort on understanding specificity of a model network system in yeast, Saccharomyces cerevisiae, which contains three mitogen-activated protein kinase (MAPK) signal transduction cascades that share multiple signaling components ...[more]

PMID: 17977559

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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:Bis-2-chloroethyl sulfide (sulfur mustard, SM) is a potent alkylating agent and vesicant. Exposure to SM results in activation of numerous signaling cascades, including mitogen-activated protein kinase (MAPK) signaling pathways. These pathways include the Erk, p38, and JNK pathways, which are involved in cell growth, inflammation, and stress signaling. However, the precise roles of these pathways in SM toxicity have not been fully elucidated. We used Western blotting and microarray analysis to examine the activation and role of each pathway following SM exposure in primary human epidermal keratinocytes. Western blotting revealed increased phosphorylation of p38 and JNK following SM exposure; however, phosphorylation of Erk was equivocal, suggesting that growth conditions may impact activation of Erk by SM. We used pharmacologic inhibitors to target each MAPK and then compared the gene expression profiles to identify SM-induced gene networks regulated by each MAPK. Cells were pretreated with 10 µM SB 203580 (p38 inhibitor), PD 98059 (Erk inhibitor), or SP 600125 (JNK inhibitor) 60 minutes before exposure to 200 µM SM. Cells were harvested at 1h, 4h, and 8h post-exposure, and RNA was extracted for synthesis of microarray probes. Probes were hybridized to Affymetrix U133 Plus 2.0 arrays for gene expression profiling. Analysis of variance was performed to identify genes significantly modulated due to pharmacologic inhibition in SM-exposed cells. Pathway mapping confirmed alterations in SM-induced Erk, JNK, and p38 MAPK signaling due to pharmacologic inhibition. SM-induced expression of IL-8, IL-6, and TNF-alpha was decreased by p38 MAPK inhibition, but not by inhibition of other MAPKs. Based on the number of significant pathways mapped to each MAPK in the presence and absence of inhibitors, the p38 MAPK pathway appeared to be the MAPK pathway most responsive to SM exposure. Interestingly, pathway mapping of the microarray data identified potential cross-talk between MAPK signaling pathways and other pathways involved in SM-induced signaling. Mining of these results will increase our understanding of the role of MAPK pathways in SM-induced signal transduction and may identify potential therapeutic targets for medical countermeasure development.

Dataset Information

Zou2007_MAPK_SignalingNetworks

Publications

Modeling specificity in the yeast MAPK signaling networks.

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