Systems biology最新文献

Computational models aid in the quantitative understanding of cell signalling networks. One important goal is to ascertain how multiple network components work together to govern cellular responses, that is, to determine cell 'signal-response' relationships. Several methods exist to study steady-state signals in the context of differential equation-based models. However, many biological networks influence cell behaviour through time-varying signals operating during a transient activated state that ultimately returns to a basal steady-state. A computational approach adapted from dynamical systems analysis to discern how diverse transient signals relate to alternative cell fates is described. Direct finite-time Lyapunov exponents (DLEs) are employed to identify phase-space domains of high sensitivity to initial conditions. These domains delineate regions exhibiting qualitatively different transient activities that would be indistinguishable using steady-state analysis but which correspond to different outcomes. These methods are applied to a physicochemical model of molecular interactions among caspase-3, caspase-8 and X-linked inhibitor of apoptosis--proteins whose transient activation determines cell death against survival fates. DLE analysis enabled identification of a separatrix that quantitatively characterises network behaviour by defining initial conditions leading to apoptotic cell death. It is anticipated that DLE analysis will facilitate theoretical investigation of phenotypic outcomes in larger models of signalling networks.

A majority of gefitinib (IRESSA)-responsive tumours in non-small cell lung cancer have been found to carry mutations in ErbB1. Previously, it has been observed that internalisation-deficient ErbB1 receptors are strong drivers of oncogenesis. Using a computational model of ErbB1 trafficking and signalling, it is found that a deficiency in ErbB1 internalisation is sufficient to explain the observed signalling phenotype of these gefitinib-responsive ErbB1 mutants in lung cancer cell lines. Experimental tests confirm that gefitinib-sensitive cell lines with and without ErbB1 mutations exhibit markedly slower internalisation rates than gefitinib-insensitive cell lines. Moreover, the computational model demonstrates that reduced ErbB1 internalisation rates are mechanistically linked to upregulated AKT signalling. Experimentally it is confirmed that impaired internalisation of ErbB1 is associated with increased AKT activity, which can be blocked by gefitinib. On the basis of these experimental and computational results, it is surmised that gefitinib sensitivity is a marker of a reliance on AKT signalling for cell survival that may be brought about by impaired ErbB1 internalisation.

Complex cellular networks regulate regeneration, detoxification and differentiation of hepatocytes. By combining experimental data with mathematical modelling, systems biology holds great promises to elucidate the key regulatory mechanisms involved and predict targets for efficient intervention. For the generation of high-quality quantitative data suitable for mathematical modelling a standardised in vitro system is essential. Therefore the authors developed standard operating procedures for the preparation and cultivation of primary mouse hepatocytes. To reliably monitor the dynamic induction of signalling pathways, the authors established starvation conditions and evaluated the extent of starvation-associated stress by quantifying several metabolic functions of cultured primary hepatocytes, namely activities of glutathione-S-transferase, glutamine synthetase, CYP3A as well as secretion of lactate and urea into the culture medium. Establishment of constant metabolic activities after an initial decrease compared with freshly isolated hepatocytes showed that the cultured hepatocytes achieve a new equilibrium state that was not affected by our starving conditions. To verify the highly reproducible dynamic activation of signalling pathways in the in vitro system, the authors examined the JAK-STAT, SMAD, PI3 kinase, MAP kinase, NF-kappaB and Wnt/beta-catenin signalling pathways. For the induction of gp130, JAK1 and STAT3 phosphorylation IL6 was used, whereas TGFbeta was applied to activate the phosphorylation of SMAD1, SMAD2 and SMAD3. Both Akt/PKB and ERK1/2 phosphorylation were stimulated by the addition of hepatocyte growth factor. The time-dependent induction of a pool of signalling competent beta-catenin was monitored in response to the inhibition of GSK3beta. To analyse whether phosphorylation is actually leading to transcriptional responses, luciferase reporter gene constructs driven by multiple copies of TGFbeta-responsive motives were applied, demonstrating a dose-dependent increase in luciferase activity. Moreover, the induction of apoptosis by the TNF-like cytokine Fas ligand was studied in the in vitro system. Thus, the mouse hepatocyte in vitro system provides an important basis for the generation of high-quality quantitative data under standardised cell culture conditions that is essential to elucidate critical hepatocellular functions by the systems biology approach.

One of the biggest problems when performing system identification of biological systems is that it is seldom possible to measure more than a small fraction of the total number of variables. If that is the case, the initial state, from where the simulation should start, has to be estimated along with the kinetic parameters appearing in the rate expressions. This is often done by introducing extra parameters, describing the initial state, and one way to eliminate them is by starting in a steady state. We report a generalisation of this approach to all systems starting on the centre manifold, close to a Hopf bifurcation. There exist biochemical systems where such data have already been collected, for example, of glycolysis in yeast. The initial value parameters are solved for in an optimisation sub-problem, for each step in the estimation of the other parameters. For systems starting in stationary oscillations, the sub-problem is solved in a straight-forward manner, without integration of the differential equations, and without the problem of local minima. This is possible because of a combination of a centre manifold and normal form reduction, which reveals the special structure of the Hopf bifurcation. The advantage of the method is demonstrated on the Brusselator.

Transforming growth factor-beta (TGFbeta) signalling is an important regulator of cellular growth and differentiation. The principal intracellular mediators of TGFbeta signalling are the Smad proteins, which upon TGFbeta stimulation accumulate in the nucleus and regulate the transcription of target genes. To investigate the mechanisms of Smad nuclear accumulation, we developed a simple mathematical model of canonical Smad signalling. The model was built using both published data and our experimentally determined cellular Smad concentrations (isoforms 2, 3 and 4). We found in mink lung epithelial cells that Smad2 (8.5-12 x 10(4) molecules cell(-1)) was present in similar amounts to Smad4 (9.3-12 x 10(4) molecules cell(-1)), whereas both were in excess of Smad3 (1.1-2.0 x 10(4) molecules cell(-1)). Variation of the model parameters and statistical analysis showed that Smad nuclear accumulation is most sensitive to parameters affecting the rates of R-Smad phosphorylation and dephosphorylation and Smad complex formation/ dissociation in the nucleus. Deleting Smad4 from the model revealed that rate-limiting phospho-R-Smad dephosphorylation could be an important mechanism for Smad nuclear accumulation. Furthermore, we observed that binding factors constitutively localised to the nucleus do not efficiently mediate Smad nuclear accumulation, if dephosphorylation is rapid. We therefore conclude that an imbalance in the rates of R-Smad phosphorylation and dephosphorylation is likely an important mechanism of Smad nuclear accumulation during TGFbeta signalling.

The glycolytic enzyme phosphoglycerate enolase (PGE) catalyses the step from 2-phosphoglycerate to phosphoenolpyruvate in glycolysis. A control analysis of PGE on growth, glycolytic flux and product formation in Lactococcus lactis subsp. lactis IL1403 is presented. A library of strains with a modulated expression of PGE from 36 to 232% relative to wildtype level was constructed. Selected strains were studied with respect to growth, glycolytic flux and product formation in a chemically defined medium. On the basis of these data, flux control coefficients of PGE on the respective fluxes were calculated. At wildtype level, PGE was found to have no significant flux control on growth, glycolytic flux or product formation, but at 36% of PGE activity relative to wildtype, the flux control on the growth rate was estimated to be C(PGE)J(micro) approximately equal to 0.7, on the glycolytic flux C(PGE)J(g) approximately equal to 0.8, on lactate formation C(PGE)J(lactate) approximately equal to 1.3, on formate formation C(PGE)J(formate) approximately equal to 0.5 and on acetate formation C(PGE) J(acetate) approximately equal to 0.25. These flux control coefficients show that the metabolism of L. lactis subsp. lactis IL1403 becomes slightly more mixed acid at reduced PGE activities. Estimation of the relative turnover of PGE indicates that excess capacity of PGE in L. lactis IL1403 may be as low as twofold.

The metabolic networks of different species show a large variety in their structural design. In this work, the evolution of functional properties of metabolism in relation with metabolic network structure is investigated. The metabolism of ancestral species is inferred from the metabolism of contemporary species using a Bayesian network model for metabolism evolution. Subsequently, these networks are analysed with the recently developed method of network expansion. This method allows for a structural analysis of metabolic networks as well as a quantification of network functions in terms of their synthesising capacities when they are provided with certain external resources. The evolutionary dynamics of one particular network function: the metabolic expansion of glucose is investigated.

Whether an allosteric feedback or feedforward modifier actually has an effect on the steady-state properties of a metabolic pathway depends not only on the allosteric modifier effect itself, but also on the control properties of the affected allosteric enzyme in the pathway of which it is part. Different modification mechanisms are analysed: mixed inhibition, allosteric inhibition and activation of the reversible Monod-Wyman-Changeux and reversible Hill models. In conclusion, it is shown that, whereas a modifier effect on substrate and product binding (specific effects) can be an effective negative feedback mechanism, it is much less effective as a positive feedforward mechanism. The prediction is that catalytic effects that change the apparent limiting velocity would be more effective in feedforward activation.

Modular approaches are powerful systems biology strategies to deal with complexity. They consist in lumping conceptually all that is irrelevant to the problem under study, leaving explicit the portions of interest. Modular (or top-down) metabolic control analysis is a theoretical and experimental approach to study the sensitivity properties of complex metabolic systems. Initially, it was conceived for infinitesimal changes but, recently, it started to be developed for large metabolic changes. A central result of this approach is that the systemic properties, represented by control coefficients, can be expressed as a function of the properties of isolated modules, the elasticity coefficients. Here we extend the theory for large changes to the case that the elasticity coefficients depend on the extent of the change. The novel theory is used to analyse experimental data related to the control of glycolytic flux in Escherichia coli. Our analysis shows that the pattern of control for large changes is quantitatively and qualitatively different from the one obtained applying the infinitesimal treatment.