A framework for mapping, visualisation and automatic model creation of signal-transduction networks.

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.

Alpha11 beta1 integrin-dependent regulation of periodontal ligament function in the erupting mouse incisor.

The fibroblast integrin alpha11beta1 is a key receptor for fibrillar collagens. To study the potential function of alpha11 in vivo, we generated a null allele of the alpha11 gene. Integrin alpha11(-/-) mice are viable and fertile but display dwarfism with increased mortality, most probably due to severely defective incisors. Mutant incisors are characterized by disorganized periodontal ligaments, whereas molar ligaments appear normal. The primary defect in the incisor ligament leads to halted tooth eruption. alpha11beta1-defective embryonic fibroblasts displayed severe defects in vitro, characterized by (i) greatly reduced cell adhesion and spreading on collagen I, (ii) reduced ability to retract collagen lattices, and (iii) reduced cell proliferation. Analysis of matrix metalloproteinase in vitro and in vivo revealed disturbed MMP13 and MMP14 synthesis in alpha11(-/-) cells. We show that alpha11beta1 is the major receptor for collagen I on mouse embryonic fibroblasts and suggest that alpha11beta1 integrin is specifically required on periodontal ligament fibroblasts for cell migration and collagen reorganization to help generate the forces needed for axial tooth movement. Our data show a unique role for alpha11beta1 integrin during tooth eruption.

Systems Level Analysis of the Yeast Osmo-Stat.

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.

Automated ensemble modeling with modelMaGe: analyzing feedback mechanisms in the Sho1 branch of the HOG pathway.

In systems biology uncertainty about biological processes translates into alternative mathematical model candidates. Here, the goal is to generate, fit and discriminate several candidate models that represent different hypotheses for feedback mechanisms responsible for downregulating the response of the Sho1 branch of the yeast high osmolarity glycerol (HOG) signaling pathway after initial stimulation. Implementing and testing these candidate models by hand is a tedious and error-prone task. Therefore, we automatically generated a set of candidate models of the Sho1 branch with the tool modelMaGe. These candidate models are automatically documented, can readily be simulated and fitted automatically to data. A ranking of the models with respect to parsimonious data representation is provided, enabling discrimination between candidate models and the biological hypotheses underlying them. We conclude that a previously published model fitted spurious effects in the data. Moreover, the discrimination analysis suggests that the reported data does not support the conclusion that a desensitization mechanism leads to the rapid attenuation of Hog1 signaling in the Sho1 branch of the HOG pathway. The data rather supports a model where an integrator feedback shuts down the pathway. This conclusion is also supported by dedicated experiments that can exclusively be predicted by those models including an integrator feedback.modelMaGe is an open source project and is distributed under the Gnu General Public License (GPL) and is available from http://modelmage.org.

Disruption of interleukin-18, but not interleukin-1, increases vulnerability to preterm delivery and fetal mortality after intrauterine inflammation.

Preterm birth is a major contributor of adverse perinatal outcome. Clinical data suggest that an inflammatory response is important in the process leading to preterm labor. By using a recently introduced mouse model of localized intrauterine lipopolysaccharide-induced inflammation, the effect of interleukin (IL)-18 gene disruption and/or IL-18 neutralization as well as combined IL-1alpha/beta gene disruption on inflammation-induced fetal loss was investigated. The frequency of preterm fetal loss was significantly higher in IL-18 knockout mice (58.9%) and in mice administered IL-18-binding protein (59.7%) compared to wild-type controls (34.7%). The rate of fetal loss was not affected by IL-1alpha/beta gene deficiency (38.7%). Decreased IL-18 protein expression combined with elevated IL-12 protein expression in uterine tissue of IL-18 knockout mice and IL-18-binding protein-treated animals was noticed. These data demonstrate that preterm pregnancy loss in response to intrauterine inflammation was enhanced by disruption of the IL-18 gene and/or IL-18 neutralization, events that may relate to exaggerated Th1 responses because of an increased IL-12/IL-18 ratio.

Identification of candidate cancer-causing genes in mouse brain tumors by retroviral tagging.

Murine retroviruses may cause malignant tumors in mice by insertional mutagenesis of host genes. The use of retroviral tagging as a means of identifying cancer-causing genes has, however, almost entirely been restricted to hematopoietic tumors. The aim of this study was to develop a system allowing for the retroviral tagging of candidate genes in malignant brain tumors. Mouse gliomas were induced by a recombinant Moloney murine leukemia virus encoding platelet-derived growth factor (PDGF) B-chain. The underlying idea was that tumors evolve through a combination of PDGF-mediated autocrine growth stimulation and insertional mutagenesis of genes that cooperate with PDGF in gliomagenesis. Common insertion sites (loci that were tagged in more than one tumor) were identified by cloning and sequencing retroviral flanking segments, followed by blast searches of mouse genome databases. A number of candidate brain tumor loci (Btls) were identified. Several of these Btls correspond to known tumor-causing genes; these findings strongly support the underlying idea of our experimental approach. Other Btls harbor genes with a hitherto unproven role in transformation or oncogenesis. Our findings indicate that retroviral tagging with a growth factor-encoding virus may be a powerful means of identifying candidate tumor-causing genes in nonhematopoietic tumors.

alpha 11beta 1 integrin recognizes the GFOGER sequence in interstitial collagens.

The integrins alpha(1)beta(1), alpha(2)beta(1), alpha(10)beta(1), and alpha(11)beta(1) are referred to as a collagen receptor subgroup of the integrin family. Recently, both alpha(1)beta(1) and alpha(2)beta(1) integrins have been shown to recognize triple-helical GFOGER (where single letter amino acid nomenclature is used, O = hydroxyproline) or GFOGER-like motifs found in collagens, despite their distinct binding specificity for various collagen subtypes. In the present study we have investigated the mechanism whereby the latest member in the integrin family, alpha(11)beta(1), recognizes collagens using C2C12 cells transfected with alpha(11) cDNA and the bacterially expressed recombinant alpha(11) I domain. The ligand binding properties of alpha(11)beta(1) were compared with those of alpha(2)beta(1). Mg(2+)-dependent alpha(11)beta(1) binding to type I collagen required micromolar Ca(2+) but was inhibited by 1 mm Ca(2+), whereas alpha(2)beta(1)-mediated binding was refractory to millimolar concentrations of Ca(2+). The bacterially expressed recombinant alpha(11) I domain preference for fibrillar collagens over collagens IV and VI was the same as the alpha(2) I domain. Despite the difference in Ca(2+) sensitivity, alpha(11)beta(1)-expressing cells and the alpha(11) I domain bound to helical GFOGER sequences in a manner similar to alpha(2)beta(1)-expressing cells and the alpha(2) I domain. Modeling of the alpha I domain-collagen peptide complexes could partially explain the observed preference of different I domains for certain GFOGER sequence variations. In summary, our data indicate that the GFOGER sequence in fibrillar collagens is a common recognition motif used by alpha(1)beta(1), alpha(2)beta(1), and also alpha(11)beta(1) integrins. Although alpha(10) and alpha(11) chains show the highest sequence identity, alpha(2) and alpha(11) are more similar with regard to collagen specificity. Future studies will reveal whether alpha(2)beta(1) and alpha(11)beta(1) integrins also show overlapping biological functions.