[Show abstract][Hide abstract] ABSTRACT: Intracellular signalling systems are highly complex. This complexity makes handling, analysis and visualisation of available knowledge a major challenge in current signalling research. Here, we present a novel framework for mapping signal-transduction networks that avoids the combinatorial explosion by breaking down the network in reaction and contingency information. It provides two new visualisation methods and automatic export to mathematical models. We use this framework to compile the presently most comprehensive map of the yeast MAP kinase network. Our method improves previous strategies by combining (I) more concise mapping adapted to empirical data, (II) individual referencing for each piece of information, (III) visualisation without simplifications or added uncertainty, (IV) automatic visualisation in multiple formats, (V) automatic export to mathematical models and (VI) compatibility with established formats. The framework is supported by an open source software tool that facilitates integration of the three levels of network analysis: definition, visualisation and mathematical modelling. The framework is species independent and we expect that it will have wider impact in signalling research on any system.
Full-text · Article · Apr 2012 · Molecular Systems Biology
[Show abstract][Hide abstract] 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.
Full-text · Article · Jun 2009 · Molecular Systems Biology
[Show abstract][Hide abstract] ABSTRACT: Extended abstract Robustness is a fundamental and ubiquitous property of complex biological systems. By being robust the system maintains its function in the face of external and internal perturbations. During evolution internal parameters such as gene expression have been optimized to allow a precise and accurate function of the system. These parameters must have permissible ranges to account for fluctuations in environmental conditions (external perturbation) or internal conditions such as noise in gene expression (internal perturbation) (1, 2). In this study we approached the problem of quantitatively measure these ranges by estimating upper limit gene copy number for 29 HOG pathway related genes in the yeast Saccharomyces cerevisiae (3). This was done using a novel genetic screening method named "genetic tug-of-war" (gTOW). This method is based on the naturally occurring 2 micron plasmid of yeast with the inserted amplification marker leu2d and a gene of interest (together with its native regulatory DNA elements). In a selective condition the plasmid copy number will increase due to the need of leucine, while at the same time the plasmid copy number will decrease if the target gene has a toxic or inhibitory effect on the cell. The two biases give rise to the term "genetic tug-of- war" or gTOW (2). In addition to estimating the plasmid copy number a phenotypic profiling of the 29 target genes was performed resulting in three different readouts: lag phase, rate of growth and efficiency of growth (4). Among the 29 studied genes the MAPKK PBS2 had the most severe growth inhibition which correlates well with previous studies on overexpression of PBS2 (5). The strain also had a low plasmid copy number (~30). This fact points toward the validity of the study and its extension to encompass the entire known signal transduction system in yeast. Especially interesting will be the most sensitive target genes which will be points of fragility in the network. The quantitative data provided could potentially also be used in existing computational models for the HOG pathway or other pathways in the signal transduction system to further deepen our knowledge about robust properties of the system.