1. |
- Carretero Chavez, Willow, et al.
(author)
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kboolnet : a toolkit for the verification, validation, and visualization of reaction-contingency (rxncon) models
- 2023
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In: BMC Bioinformatics. - : BioMed Central (BMC). - 1471-2105. ; 24:1
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Journal article (peer-reviewed)abstract
- BACKGROUND: Computational models of cell signaling networks are extremely useful tools for the exploration of underlying system behavior and prediction of response to various perturbations. By representing signaling cascades as executable Boolean networks, the previously developed rxncon ("reaction-contingency") formalism and associated Python package enable accurate and scalable modeling of signal transduction even in large (thousands of components) biological systems. The models are split into reactions, which generate states, and contingencies, that impinge on reactions; this avoids the so-called "combinatorial explosion" of system size. Boolean description of the biological system compensates for the poor availability of kinetic parameters which are necessary for quantitative models. Unfortunately, few tools are available to support rxncon model development, especially for large, intricate systems.RESULTS: We present the kboolnet toolkit ( https://github.com/Kufalab-UCSD/kboolnet , complete documentation at https://github.com/Kufalab-UCSD/kboolnet/wiki ), an R package and a set of scripts that seamlessly integrate with the python-based rxncon software and collectively provide a complete workflow for the verification, validation, and visualization of rxncon models. The verification script VerifyModel.R checks for responsiveness to repeated stimulations as well as consistency of steady state behavior. The validation scripts TruthTable.R, SensitivityAnalysis.R, and ScoreNet.R provide various readouts for the comparison of model predictions to experimental data. In particular, ScoreNet.R compares model predictions to a cloud-stored MIDAS-format experimental database to provide a numerical score for tracking model accuracy. Finally, the visualization scripts allow for graphical representations of model topology and behavior. The entire kboolnet toolkit is cloud-enabled, allowing for easy collaborative development; most scripts also allow for the extraction and analysis of individual user-defined "modules".CONCLUSION: The kboolnet toolkit provides a modular, cloud-enabled workflow for the development of rxncon models, as well as their verification, validation, and visualization. This will enable the creation of larger, more comprehensive, and more rigorous models of cell signaling using the rxncon formalism in the future.
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2. |
- Herrgård, Markus J, et al.
(author)
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A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology
- 2008
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In: Nature Biotechnology. ; 26:10, s. 1155-1160
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Journal article (peer-reviewed)abstract
- Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and content, and use different terminologies to describe the same chemical entities. This make comparisons between them difficult and underscores the desirability of a consolidated metabolic network that collects and formalizes the 'community knowledge' of yeast metabolism. We describe how we have produced a consensus metabolic network reconstruction for S. cerevisiae. In drafting it, we placed special emphasis on referencing molecules to persistent databases or using database-independent forms, such as SMILES or InChl strings, as this permits their chemical structure to be represented unambiguously and in a manner that permits automated reasoning. The reconstruction is readily available via a publicly accessible database and in the Systems Biology Markup Language (http://www.comp-sys-bio.org/yeastnet). It can be maintained as a resource that serves as a common denominator for studying the systems biology of yeast. Similar strategies should benefit communities studying genome-scale metabolic networks of other organisms.
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3. |
- Klipp, Edda, et al.
(author)
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Integrative model of the response of yeast to osmotic shock
- 2005
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In: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 23:8
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Journal article (peer-reviewed)abstract
- Integration of experimental studies with mathematical modeling allows insight into systems properties, prediction of perturbation effects and generation of hypotheses for further research. We present a comprehensive mathematical description of the cellular response of yeast to hyperosmotic shock. The model integrates a biochemical reaction network comprising receptor stimulation, mitogen-activated protein kinase cascade dynamics, activation of gene expression and adaptation of cellular metabolism with a thermodynamic description of volume regulation and osmotic pressure. Simulations agree well with experimental results obtained under different stress conditions or with specific mutants. The model is predictive since it suggests previously unrecognized features of the system with respect to osmolyte accumulation and feedback control, as confirmed with experiments. The mathematical description presented is a valuable tool for future studies on osmoregulation in yeast and—with appropriate modifications—other organisms. It also serves as a starting point for a comprehensive description of cellular signaling.
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4. |
- Klipp, Edda, et al.
(author)
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Shutting the MAP off - and on again?
- 2004
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In: Current Genomics. - 1389-2029. ; 5:8, s. 637-647
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Journal article (peer-reviewed)abstract
- Signal transduction pathways are the cellular information routes with which cells monitor their surrounding as well as their own state and adjust to environmental changes or hormonal stimuli. MAP kinase pathways are one type of signalling systems in eukaryotes that control stress responses, cell growth and proliferation as well as differentiation. In this study we compare two very well studied yeast signalling systems, the pheromone response pathway and the osmosensing HOG pathway. We have recently generated mathematical models that allow in silico analysis of signalling properties for both pathways. Deactivation of signalling is as important as activation because inappropriate pathway activation causes cell cycle arrest (in the cases studied here) or uncontrolled proliferation. Both pathways are transiently activated by their stimulus, i.e. mating pheromone and osmostress, respectively, indicating rigorous feedback mechanisms. However, the HOG pathway can readily be reactivated by a subsequent stimulus and this is important for its biological role in mediating osmoadaptation. The pheromone response pathway, however, is desensitised and is unable to respond for a certain period of time. While some mechanisms of feedback control are similar in both systems (such as the downregulatory, role of protein phosphatases) the main difference seems to lie in the control of the sensors/receptors. The pheromone receptors are internalised and degraded following stimulation and hence are not available for further stimulation. The osmosensors on the other hand, seem to toggle between activated and deactivated state only controlled by osmotic changes. Together with subtle control by protein phosphatases this results in a system that is constantly receptive for stimulation.
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5. |
- Krantz, Marcus, 1975, et al.
(author)
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Robustness and fragility in the high osmolarity glycerol (HOG) pathway in S. cerevisiae
- 2009
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In: 10th International Conference on Systems Biology (ICSB2009) proceedings, 10th International Conference on Systems Biology (ICSB2009), Aug 30 - Sep 4, Stanford, California, USA.
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Conference paper (other academic/artistic)abstract
- Cellular signalling networks integrate environmental stimuli with information on cellular status. These networks must be robust against stochastic fluctuations in external stimuli as well as in the amounts of signalling components. Here [1], we challenge the yeast HOG signal transduction pathway with systematic perturbations in components’ expression levels implemented by a “genetic tug-of-war” methodology under various external conditions in search of nodes of fragilities. We observe a substantially higher frequency of fragile nodes in this signal transduction pathway than has been observed for other cellular processes. These fragilities disperse without any clear pattern over biochemical functions or location in pathway topology, with the most sensitive nodes being the proteins PBS2 and SSK1. They are also largely independent of pathway activation by external stimuli. However, the strongest toxicities are caused by pathway hyperactivation. We studied the influence of seven regulatory motifs around these HOG pathway components in silico through ODE models. Based on the SLN1 and the MAPK modules of a mathematical model of osmoregulation in budding yeast by Klipp et al. [2] we included new motifs and fitted the affected parameters to time courses of dually phosphorylated Hog1p generated by the original model under stress and stress-free conditions. The regulations taken into account by our analysis include Pbs2p scaffolding, Ssk1p and Pbs2p autoactivation, and the formation of a stable dimer between Ssk2p and Ssk1p. A subsequent sensitivity analysis identified Pbs2's role as a scaffold protein and Ssk1p-Ssk2p dimerization as the important contributors to the observed robustness pattern in silico. Thus, in vivo robustness data can be used to discriminate and improve mathematical models.
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6. |
- Krantz, Marcus, 1975, et al.
(author)
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Robustness and fragility in the yeast high osmolarity glycerol (HOG) signal-transduction pathway.
- 2009
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In: Molecular systems biology. - : EMBO. - 1744-4292. ; 5
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Journal article (peer-reviewed)abstract
- Cellular signalling networks integrate environmental stimuli with the information on cellular status. These networks must be robust against stochastic fluctuations in stimuli as well as in the amounts of signalling components. Here, we challenge the yeast HOG signal-transduction pathway with systematic perturbations in components' expression levels under various external conditions in search for nodes of fragility. We observe a substantially higher frequency of fragile nodes in this signal-transduction pathway than that has been observed for other cellular processes. These fragilities disperse without any clear pattern over biochemical functions or location in pathway topology and they are largely independent of pathway activation by external stimuli. However, the strongest toxicities are caused by pathway hyperactivation. In silico analysis highlights the impact of model structure on in silico robustness, and suggests complex formation and scaffolding as important contributors to the observed fragility patterns. Thus, in vivo robustness data can be used to discriminate and improve mathematical models.
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7. |
- Kuehn, Clemens, et al.
(author)
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Exploring the impact of osmoadaptation on glycolysis using time-varying response-coefficients
- 2008
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In: Genome informatics. International Conference on Genome Informatics. - 0919-9454. ; 20, s. 77-90
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Conference paper (peer-reviewed)abstract
- We present a model of osmoadaptation in S.cerevisiae based on existing experimental and theoretical work. In order to investigate the impact of osmoadaptation on glycolysis, this model focuses on the interactions between glycolysis and osmoadaptation, namely the production of glycerol and its influence on flux towards pyruvate. Evaluation of this model shows that, depending on initial relations between glycerol and pyruvate production, the increased glycerol production can have a substantial negative effect on the pyruvate production rate. Existing experimental data and a detailed analysis of the model lead to the suggestion of an interaction between activated Hog1 and activators of glycolysis such as Pfk26.
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8. |
- Kühn, Clemens, 1981, et al.
(author)
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Formal Representation of the High Osmolarity Glycerol Pathway in Yeast
- 2009
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In: Genome informatics. International Conference on Genome Informatics. - 0919-9454. ; 22, s. 69-83
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Journal article (peer-reviewed)abstract
- The high osmolarity glycerol (HOG) signalling system in yeast belongs to the class of Mitogen Activated Protein Kinase (MAPK) pathways that are found in all eukaryotic organisms. It includes at least three scaffold proteins that form complexes, and involves reactions that are strictly dependent on the set of species bound to a certain complex. The scaffold proteins lead to a combinatorial increase in the number of possible states. To date, representations of the HOG pathway have used simplifying assumptions to avoid this combinatorial problem. Such assumptions are hard to make and may obscure or remove essential properties of the system.This paper presents a detailed generic formal representation of the HOG system without such assumptions, showing the molecular interactions known from the literature. The model takes complexes into account, and summarises existing knowledge in an unambiguous and detailed representation. It can thus be used to anchor discussions about the HOG system. In the commonly used Systems Biology Markup Language (SBML), such a model would need to explicitly enumerate all state variables. The \emph{Kappa} modelling language which we use supports representation of complexes without such enumeration.To conclude, we compare \emph{Kappa} with a few other modelling languages and software tools that could also be used to represent and model the HOG system.
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9. |
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10. |
- Nordlander, Bodil, 1976, et al.
(author)
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Modelling signalling pathways-A yeast approach
- 2005
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In: In Alberghina L, Westerhoff H (eds) “Systems Biology”. In the series “Topics in Current Genetics” (vol 13, Hohmann S, Ed). - Berlin, Heidelberg : Springer Berlin Heidelberg. ; , s. 277-304
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Book chapter (other academic/artistic)
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