Death wins against life in a spatially extended model of the caspase-3/8 feedback loop.

Apoptosis is an important physiological process which enables organisms to remove unwanted or damaged cells. A mathematical model of the extrinsic pro-apoptotic signaling pathway has been introduced by Eissing et al. (2007) and a bistable behavior with a stable death state and a stable life state of the reaction system has been established. In this paper, we consider a spatial extension of the extrinsic pro-apoptotic signaling pathway incorporating diffusion terms and make a model-based, numerical analysis of the apoptotic switch in the spatial dimension. For the parameter regimes under consideration it turns out that for this model diffusion homogenizes rapidly the concentrations which afterward are governed by the original reaction system. The activation of effector-caspase 3 depends on the space averaged initial concentration of pro-caspase 8 and pro-caspase 3 at the beginning of the process.

Design of biomolecular network modifications to achieve adaptation.

A biomolecular network is called adaptive if its output returns to the original value after a transient response even under a persisting stimulus. The conditions for adaptation have been investigated thoroughly with systems theory approaches in the literature and it is easy to check whether they are satisfied in the linear approximation. In contrast, it is in general not easy to modify a non-adaptive network model such that it gains adaptive behaviour, especially for medium- and large-scale networks. The authors present a systematic approach based on the notion of kinetic perturbations to construct adaptive biomolecular network models from non-adaptive ones. An advantage of kinetic perturbations in this application is that neither the stoichiometry nor the steady state of the system is changed. Furthermore, the method covers both parameter and network structure modifications and can be applied to any reaction rate formalism and even to medium-scale or partially unknown models. The approach is exemplified at a small- and a medium-sized biomolecular network, illustrating its potential to systematically evaluate the different network modifications for adaptation. The proposed method will be useful either in iterative model building to construct mathematical models of adaptive biomolecular networks, or in synthetic biology where it can be applied to design or modify synthetic networks for adaptation.

Parameter identification, experimental design and model falsification for biological network models using semidefinite programming.

One of the most challenging tasks in systems biology is parameter identification from experimental data. In particular, if the available data are noisy, the resulting parameter uncertainty can be huge and should be quantified. In this work, a set-based approach for parameter identification in discrete time models of biochemical reaction networks from time series data is developed. The basic idea is to determine an outer approximation to the set of parameters for which trajectories are consistent with the available data. In order to approximate the set of consistent parameters (SCP) a feasibility problem is derived. This feasibility problem is used to verify that complete parameter sets cannot contain consistent parameters. This method is very appealing because instead of checking a finite number of distinct points, complete sets are analysed. With this approach, model falsification simply corresponds to showing that the SCP is empty. Besides parameter identification, a novel set-based method for experimental design is presented. This method yields reliable predictions on the information content of future measurements also for the case of very limited a priori knowledge and uncertain inputs. The properties of the method are presented using a discrete time model of the MAP kinase cascade.

Cell differentiation modeled via a coupled two-switch regulatory network.

Mesenchymal stem cells can give rise to bone and other tissue cells, but their differentiation still escapes full control. In this paper we address this issue by mathematical modeling. We present a model for a genetic switch determining the cell fate of progenitor cells which can differentiate into osteoblasts (bone cells) or chondrocytes (cartilage cells). The model consists of two switch mechanisms and reproduces the experimentally observed three stable equilibrium states: a progenitor, an osteogenic, and a chondrogenic state. Conventionally, the loss of an intermediate (progenitor) state and the entailed attraction to one of two opposite (differentiated) states is modeled as a result of changing parameters. In our model in contrast, we achieve this by distributing the differentiation process to two functional switch parts acting in concert: one triggering differentiation and the other determining cell fate. Via stability and bifurcation analysis, we investigate the effects of biochemical stimuli associated with different system inputs. We employ our model to generate differentiation scenarios on the single cell as well as on the cell population level. The single cell scenarios allow to reconstruct the switching upon extrinsic signals, whereas the cell population scenarios provide a framework to identify the impact of intrinsic properties and the limiting factors for successful differentiation.

Cystic fibrosis screening in neonates--measurement of immunoreactive trypsin and direct genotype analysis for delta F508 mutation.

This study investigated the clinical usefulness of screening for cystic fibrosis (CF) in 19,992 newborns, over 39 months, in an Austrian population. Immunoreactive serum trypsin (IRT) determination was followed by sweat chloride analysis (sweat test) to establish diagnosis. In a retrospective analysis covering 6 months of the study period, individuals who were considered to be at risk after IRT estimation (n = 22) were analysed for delta F508 mutation, using a new method of DNA extraction from the initial dried blood specimens. A total of 119 infants (0.6%) had values greater than 750 ng trypsin/ml whole blood. In 88 babies sweat tests were performed, leading to the diagnosis of CF in 11 cases. One patient was not initially identified by screening but was later discovered due to his clinical status. Three infants were noted to carry the delta F508 mutation (1 homozygous, 2 heterozygous). Two of these babies already had CF. The second heterozygote was a carrier. A highly efficient three tier screening strategy is presented in which IRT estimation, determination of delta F508 status and sweat chloride testing could lead to a high sensitivity analysis of this population.