References of "Sauter, Thomas 50002988"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailCombinatorial regulation of lipoprotein lipase by microRNAs during mouse adipogenesis
Liivrand, Maria UL; Heinäniemi, Merja UL; John, Elisabeth UL et al

in RNA Biology (2014), 11(1), 76-91

MicroRNAs (miRNAs) regulate gene expression directly through base pairing to their targets or indirectly through participating in multi-scale regulatory networks. Often miRNAs take part in feed-forward ... [more ▼]

MicroRNAs (miRNAs) regulate gene expression directly through base pairing to their targets or indirectly through participating in multi-scale regulatory networks. Often miRNAs take part in feed-forward motifs where a miRNA and a transcription factor act on shared targets to achieve accurate regulation of processes such as cell differentiation. Here we show that the expression levels of miR-27a and miR-29a inversely correlate with the mRNA levels of lipoprotein lipase (Lpl), their predicted combinatorial target, and its key transcriptional regulator peroxisome proliferator activated receptor gamma (Pparg) during 3T3-L1 adipocyte differentiation. More importantly, we show that Lpl, a key lipogenic enzyme, can be negatively regulated by the two miRNA families in a combinatorial fashion on the mRNA and functional level in maturing adipocytes. This regulation is mediated through the Lpl 3′UTR as confirmed by reporter gene assays. In addition, a small mathematical model captures the dynamics of this feed-forward motif and predicts the changes in Lpl mRNA levels upon network perturbations. The obtained results might offer an explanation to the dysregulation of LPL in diabetic conditions and could be extended to quantitative modeling of regulation of other metabolic genes under similar regulatory network motifs. [less ▲]

Detailed reference viewed: 251 (34 UL)
Full Text
Peer Reviewed
See detailFast reconstruction of compact context-specific metabolic network models
Vlassis, Nikos UL; Pacheco, Maria UL; Sauter, Thomas UL

in PLoS Computational Biology (2014), 10(1), 1003424

Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can ... [more ▼]

Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can routinely involve large numbers of tests under different conditions and extensive parameter tuning, which calls for fast algorithms. We present FASTCORE, a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X. FASTCORE takes as input a core set of reactions that are known to be active in the context of interest (e.g., cell or tissue), and it searches for a flux consistent subnetwork of the global network that contains all reactions from the core set and a minimal set of additional reactions. Our key observation is that a minimal consistent reconstruction can be defined via a set of sparse modes of the global network, and FASTCORE iteratively computes such a set via a series of linear programs. Experiments on liver data demonstrate speedups of several orders of magnitude, and significantly more compact reconstructions, over a rival method. Given its simplicity and its excellent performance, FASTCORE can form the backbone of many future metabolic network reconstruction algorithms. [less ▲]

Detailed reference viewed: 239 (30 UL)
Full Text
Peer Reviewed
See detailA mathematical model of metabolism and regulation provides a systems-level view of how Escherichia coli responds to oxygen
Ederer, M; Steinsiek, S; Stagge, S et al

in Frontiers in Microbiology (2014), 5(124),

The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of ... [more ▼]

The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of energy supply, carbon, and redox metabolism. The measurement of transcript levels, metabolite concentrations and metabolic fluxes per se gives an incomplete picture. An appreciation of the interdependencies between the different measurement values is essential for systems-level understanding. Mathematical modeling has the potential to provide a coherent and quantitative description of the interplay between gene expression, metabolite concentrations, and metabolic fluxes. Escherichia coli undergoes major adaptations in central metabolism when the availability of oxygen changes. Thus, an integrated description of the oxygen response provides a benchmark of our understanding of carbon, energy, and redox metabolism. We present the first comprehensive model of the central metabolism of E. coli that describes steady-state metabolism at different levels of oxygen availability. Variables of the model are metabolite concentrations, gene expression levels, transcription factor activities, metabolic fluxes, and biomass concentration. We analyze the model with respect to the production capabilities of central metabolism of E. coli. In particular, we predict how precursor and biomass concentration are affected by product formation. - See more at: http://journal.frontiersin.org/Journal/10.3389/fmicb.2014.00124/abstract#sthash.Ocu5zSDe.dpuf [less ▲]

Detailed reference viewed: 141 (11 UL)
Full Text
Peer Reviewed
See detailBasic Regulatory Principles of Escherichia coli's Electron Transport Chain for Varying Oxygen Conditions.
Henkel, Sebastian G.; Beek, Alexander Ter; Steinsiek, Sonja et al

in PloS one (2014), 9(9), 107640

For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known that the ... [more ▼]

For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known that the global transcriptional regulators FNR and ArcA are involved in oxygen response it is unclear how they interplay in the regulation of ETC enzymes under micro-aerobic chemostat conditions. Also, there are diverse results which and how quinones (oxidised/reduced, ubiquinone/other quinones) are controlling the ArcBA two-component system. In the following a mathematical model of the E. coli ETC linked to basic modules for substrate uptake, fermentation product excretion and biomass formation is introduced. The kinetic modelling focusses on regulatory principles of the ETC for varying oxygen conditions in glucose-limited continuous cultures. The model is based on the balance of electron donation (glucose) and acceptance (oxygen or other acceptors). Also, it is able to account for different chemostat conditions due to changed substrate concentrations and dilution rates. The parameter identification process is divided into an estimation and a validation step based on previously published and new experimental data. The model shows that experimentally observed, qualitatively different behaviour of the ubiquinone redox state and the ArcA activity profile in the micro-aerobic range for different experimental conditions can emerge from a single network structure. The network structure features a strong feed-forward effect from the FNR regulatory system to the ArcBA regulatory system via a common control of the dehydrogenases of the ETC. The model supports the hypothesis that ubiquinone but not ubiquinol plays a key role in determining the activity of ArcBA in a glucose-limited chemostat at micro-aerobic conditions. [less ▲]

Detailed reference viewed: 111 (2 UL)
Full Text
Peer Reviewed
See detailIdentification of New IkappaBalpha Complexes by an Iterative Experimental and Mathematical Modeling Approach.
Konrath, Fabian; Witt, Johannes; Sauter, Thomas UL et al

in PLoS computational biology (2014), 10(3), 1003528

The transcription factor nuclear factor kappa-B (NFkappaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFkappaB activity may contribute to the ... [more ▼]

The transcription factor nuclear factor kappa-B (NFkappaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFkappaB activity may contribute to the development of severe diseases when the regulatory system is impaired. Since NFkappaB can be triggered by a huge variety of inflammatory, pro-and anti-apoptotic stimuli, its activation underlies a complex and tightly regulated signaling network that also includes multi-layered negative feedback mechanisms. Detailed understanding of this complex signaling network is mandatory to identify sensitive parameters that may serve as targets for therapeutic interventions. While many details about canonical and non-canonical NFkappaB activation have been investigated, less is known about cellular IkappaBalpha pools that may tune the cellular NFkappaB levels. IkappaBalpha has so far exclusively been described to exist in two different forms within the cell: stably bound to NFkappaB or, very transiently, as unbound protein. We created a detailed mathematical model to quantitatively capture and analyze the time-resolved network behavior. By iterative refinement with numerous biological experiments, we yielded a highly identifiable model with superior predictive power which led to the hypothesis of an NFkappaB-lacking IkappaBalpha complex that contains stabilizing IKK subunits. We provide evidence that other but canonical pathways exist that may affect the cellular IkappaBalpha status. This additional IkappaBalpha:IKKgamma complex revealed may serve as storage for the inhibitor to antagonize undesired NFkappaB activation under physiological and pathophysiological conditions. [less ▲]

Detailed reference viewed: 78 (7 UL)
Full Text
Peer Reviewed
See detailIntegrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network
Galhardo, Mafalda Sofia UL; Sinkkonen, Lasse UL; Berninger, Philippe et al

in Nucleic Acids Research (2013)

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied ... [more ▼]

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraintbased modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) c, CCAAT/enhancer binding protein (CEBP) a, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-phosphateacyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions. [less ▲]

Detailed reference viewed: 206 (27 UL)
Full Text
Peer Reviewed
See detailRecent development and biomedical applications of probabilistic Boolean networks
Trairatphisan, Panuwat UL; Mizera, Andrzej UL; Pang, Jun UL et al

in Cell Communication and Signaling (2013), 11(46),

Probabilistic Boolean network (PBN) modelling is a semi-quantitative approach widely used for the study of the topology and dynamic aspects of biological systems. The combined use of rule-based ... [more ▼]

Probabilistic Boolean network (PBN) modelling is a semi-quantitative approach widely used for the study of the topology and dynamic aspects of biological systems. The combined use of rule-based representation and probability makes PBN appealing for large-scale modelling of biological networks where degrees of uncertainty need to be considered. A considerable expansion of our knowledge in the field of theoretical research on PBN can be observed over the past few years, with a focus on network inference, network intervention and control. With respect to areas of applications, PBN is mainly used for the study of gene regulatory networks though with an increasing emergence in signal transduction, metabolic, and also physiological networks. At the same time, a number of computational tools, facilitating the modelling and analysis of PBNs, are continuously developed. A concise yet comprehensive review of the state-of-the-art on PBN modelling is offered in this article, including a comparative discussion on PBN versus similar models with respect to concepts and biomedical applications. Due to their many advantages, we consider PBN to stand as a suitable modelling framework for the description and analysis of complex biological systems, ranging from molecular to physiological levels. [less ▲]

Detailed reference viewed: 263 (32 UL)
Full Text
See detailMathematical modelling of the Platelet-Derived Growth Factor (PDGF) signalling pathway
Mizera, Andrzej UL; Pang, Jun UL; Sauter, Thomas UL et al

in Proceedings of 4th Workshop on Computational Models for Cell Processes (CompMod'13) (2013)

Detailed reference viewed: 94 (10 UL)
Full Text
Peer Reviewed
See detailA balancing act: Parameter estimation for biological models with steady-state measurements
Mizera, Andrzej UL; Pang, Jun UL; Sauter, Thomas UL et al

in Proceedings of 11th Conference on Computational Methods in Systems Biology (CMSB'13) (2013)

Detailed reference viewed: 82 (8 UL)
See detailFast reconstruction of compact context-specific metabolic network models
Vlassis, Nikos UL; Pacheco, Maria UL; Sauter, Thomas UL

E-print/Working paper (2013)

Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can ... [more ▼]

Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can routinely involve large numbers of tests under different conditions and extensive parameter tuning, which calls for fast algorithms. We present FASTCORE, a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X. FASTCORE takes as input a core set of reactions that are known to be active in the context of interest (e.g., cell or tissue), and it searches for a flux consistent subnetwork of the global network that contains all reactions from the core set and a minimal set of additional reactions. Our key observation is that a minimal consistent reconstruction can be defined via a set of sparse modes of the global network, and FASTCORE iteratively computes such a set via a series of linear programs. Experiments on liver data demonstrate speedups of several orders of magnitude, and significantly more compact reconstructions, over a chief rival method. Given its simplicity and its excellent performance, FASTCORE can form the backbone of many future metabolic network reconstruction algorithms. [less ▲]

Detailed reference viewed: 114 (15 UL)
Full Text
Peer Reviewed
See detailSwitch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition.
Baumuratova, Tatiana UL; Dobre, Simona; Bastogne, Thierry et al

in PloS one (2013), 8(12), 82973

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly ... [more ▼]

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits. [less ▲]

Detailed reference viewed: 121 (4 UL)
Full Text
Peer Reviewed
See detailFastcore: An algorithm for fast reconstruction of context-specific metabolic network models
Vlassis, Nikos UL; Pacheco, Maria UL; Sauter, Thomas UL

in Proc. 8th BeNeLux Bioinformatics Conference (2013)

Detailed reference viewed: 206 (36 UL)
Full Text
Peer Reviewed
See detailSystems analysis of transcription factor activities in environments with stable and dynamic oxygen concentrations
Rolfe, MD; Ocone, A; Stapleton, MR et al

in Open Biology (2012), 2(7), 120091

Understanding gene regulation requires knowledge of changes in transcription factor (TF) activities. Simultaneous direct measurement of numerous TF activities is currently impossible. Nevertheless ... [more ▼]

Understanding gene regulation requires knowledge of changes in transcription factor (TF) activities. Simultaneous direct measurement of numerous TF activities is currently impossible. Nevertheless, statistical approaches to infer TF activities have yielded non-trivial and verifiable predictions for individual TFs. Here, global statistical modelling identifies changes in TF activities from transcript profiles of Escherichia coli growing in stable (fixed oxygen availabilities) and dynamic (changing oxygen availability) environments. A core oxygen-responsive TF network, supplemented by additional TFs acting under specific conditions, was identified. The activities of the cytoplasmic oxygen-responsive TF, FNR, and the membrane-bound terminal oxidases implied that, even on the scale of the bacterial cell, spatial effects significantly influence oxygen-sensing. Several transcripts exhibited asymmetrical patterns of abundance in aerobic to anaerobic and anaerobic to aerobic transitions. One of these transcripts, ndh, encodes a major component of the aerobic respiratory chain and is regulated by oxygen-responsive TFs ArcA and FNR. Kinetic modelling indicated that ArcA and FNR behaviour could not explain the ndh transcript profile, leading to the identification of another TF, PdhR, as the source of the asymmetry. Thus, this approach illustrates how systematic examination of regulatory responses in stable and dynamic environments yields new mechanistic insights into adaptive processes. [less ▲]

Detailed reference viewed: 89 (6 UL)
Full Text
Peer Reviewed
See detailAnalysing the role of UVB-induced translational inhibition and PP2Ac deactivation in NF-kappaB signalling using a minimal mathematical model.
Witt, Johannes; Konrath, Fabian; Sawodny, Oliver et al

in PLoS ONE (2012), 7(7), 40274

Activation of nuclear factor kappaB (NF-kappaB) by interleukin-1beta (IL-1) usually results in an anti-apoptotic activity that is rapidly terminated by a negative feedback loop involving NF-kappaB ... [more ▼]

Activation of nuclear factor kappaB (NF-kappaB) by interleukin-1beta (IL-1) usually results in an anti-apoptotic activity that is rapidly terminated by a negative feedback loop involving NF-kappaB dependent resynthesis of its own inhibitor IkappaBalpha. However, apoptosis induced by ultraviolet B radiation (UVB) is not attenuated, but significantly enhanced by co-stimulation with IL-1 in human epithelial cells. Under these conditions NF-kappaB remains constitutively active and turns into a pro-apoptotic factor by selectively repressing anti-apoptotic genes. Two different mechanisms have been separately proposed to explain UV-induced lack of IkappaBalpha recurrence: global translational inhibition as well as deactivation of the Ser/Thr phosphatase PP2Ac. Using mathematical modelling, we show that the systems behaviour requires a combination of both mechanisms, and we quantify their contribution in different settings. A mathematical model including both mechanisms is developed and fitted to various experimental data sets. A comparison of the model results and predictions with model variants lacking one of the mechanisms shows that both mechanisms are present in our experimental setting. The model is successfully validated by the prediction of independent data. Weak constitutive IKKbeta phosphorylation is shown to be a decisive process in IkappaBalpha degradation induced by UVB stimulation alone, but irrelevant for (co-)stimulations with IL-1. In silico knockout experiments show that translational inhibition is predominantly responsible for lack of IkappaBalpha recurrence following IL-1+UVB stimulation. In case of UVB stimulation alone, cooperation of both processes causes the observed decrease of IkappaBalpha. This shows that the processes leading to activation of transcription factor NF-kappaB upon stimulation with ultraviolet B radiation with and without interleukin-1 costimulation are more complex than previously thought, involving both a cross talk of UVB induced translational inhibition and PP2Ac deactivation. The importance of each of the mechanisms depends on the specific cellular setting. [less ▲]

Detailed reference viewed: 66 (4 UL)
Full Text
Peer Reviewed
See detailProbabilistic model checking of the PDGF signaling pathway
Yuan, Qixia UL; Trairatphisan, Panuwat UL; Pang, Jun UL et al

in Transactions on Computational Systems Biology (2012), XIV

Detailed reference viewed: 136 (16 UL)
Full Text
Peer Reviewed
See detailA study of the PDGF signaling pathway with PRISM
Yuan, Qixia UL; Pang, Jun UL; Mauw, Sjouke UL et al

in Proceedings of the 3rd Workshop on Computational Models for Cell Processes (2011), EPTCS 67

Detailed reference viewed: 130 (13 UL)
Full Text
Peer Reviewed
See detailModeling time delay in the NFkappaB signaling pathway following low dose IL-1 stimulation.
Witt, Johannes; Barisic, Sandra; Sawodny, Oliver et al

in EURASIP Journal on Bioinformatics & Systems Biology (2011), 2011(1), 3

Stimulation of human epithelial cells with IL-1 (10 ng/ml) + UVB radiation results in sustained NFkappaB activation caused by continuous IKKbeta phosphorylation. We have recently published a strictly ... [more ▼]

Stimulation of human epithelial cells with IL-1 (10 ng/ml) + UVB radiation results in sustained NFkappaB activation caused by continuous IKKbeta phosphorylation. We have recently published a strictly reduced ordinary differential equation model elucidating the involved mechanisms. Here, we compare model extensions for low IL-1 doses (0.5 ng/ml), where delayed IKKbeta phosphorylation is observed. The extended model including a positive regulatory element, most likely auto-ubiquitination of TRAF6, reproduces the observed experimental data most convincingly. The extension is shown to be consistent with the original model and contains very sensitive processes which may serve as potential intervention targets. [less ▲]

Detailed reference viewed: 42 (0 UL)
Full Text
Peer Reviewed
See detailA systems biology approach to analyse leaf carbohydrate metabolism in Arabidopsis thaliana.
Henkel, Sebastian; Nagele, Thomas; Hormiller, Imke et al

in EURASIP Journal on Bioinformatics & Systems Biology (2011), 2011(1), 2

Plant carbohydrate metabolism comprises numerous metabolite interconversions, some of which form cycles of metabolite degradation and re-synthesis and are thus referred to as futile cycles. In this study ... [more ▼]

Plant carbohydrate metabolism comprises numerous metabolite interconversions, some of which form cycles of metabolite degradation and re-synthesis and are thus referred to as futile cycles. In this study, we present a systems biology approach to analyse any possible regulatory principle that operates such futile cycles based on experimental data for sucrose (Scr) cycling in photosynthetically active leaves of the model plant Arabidopsis thaliana. Kinetic parameters of enzymatic steps in Scr cycling were identified by fitting model simulations to experimental data. A statistical analysis of the kinetic parameters and calculated flux rates allowed for estimation of the variability and supported the predictability of the model. A principal component analysis of the parameter results revealed the identifiability of the model parameters. We investigated the stability properties of Scr cycling and found that feedback inhibition of enzymes catalysing metabolite interconversions at different steps of the cycle have differential influence on stability. Applying this observation to futile cycling of Scr in leaf cells points to the enzyme hexokinase as an important regulator, while the step of Scr degradation by invertases appears subordinate. [less ▲]

Detailed reference viewed: 115 (0 UL)
Full Text
Peer Reviewed
See detailMathematical modeling of the central carbohydrate metabolism in Arabidopsis reveals a substantial regulatory influence of vacuolar invertase on whole plant carbon metabolism.
Nagele, Thomas; Henkel, Sebastian; Hormiller, Imke et al

in Plant Physiology (2010), 153(1), 260-72

A mathematical model representing metabolite interconversions in the central carbohydrate metabolism of Arabidopsis (Arabidopsis thaliana) was developed to simulate the diurnal dynamics of primary carbon ... [more ▼]

A mathematical model representing metabolite interconversions in the central carbohydrate metabolism of Arabidopsis (Arabidopsis thaliana) was developed to simulate the diurnal dynamics of primary carbon metabolism in a photosynthetically active plant leaf. The model groups enzymatic steps of central carbohydrate metabolism into blocks of interconverting reactions that link easily measurable quantities like CO(2) exchange and quasi-steady-state levels of soluble sugars and starch. When metabolite levels that fluctuate over diurnal cycles are used as a basic condition for simulation, turnover rates for the interconverting reactions can be calculated that approximate measured metabolite dynamics and yield kinetic parameters of interconverting reactions. We used experimental data for Arabidopsis wild-type plants, accession Columbia, and a mutant defective in vacuolar invertase, AtbetaFruct4, as input data. Reducing invertase activity to mutant levels in the wild-type model led to a correct prediction of increased sucrose levels. However, additional changes were needed to correctly simulate levels of hexoses and sugar phosphates, indicating that invertase knockout causes subsequent changes in other enzymatic parameters. Reduction of invertase activity caused a decline in photosynthesis and export of reduced carbon to associated metabolic pathways and sink organs (e.g. roots), which is in agreement with the reported contribution of vacuolar invertase to sink strength. According to model parameters, there is a role for invertase in leaves, where futile cycling of sucrose appears to have a buffering effect on the pools of sucrose, hexoses, and sugar phosphates. Our data demonstrate that modeling complex metabolic pathways is a useful tool to study the significance of single enzyme activities in complex, nonintuitive networks. [less ▲]

Detailed reference viewed: 105 (1 UL)
Full Text
Peer Reviewed
See detailAnalysis of an apoptotic core model focused on experimental design using artificial data.
Schlatter, R.; Conzelmann, H.; Gilles, E. D. et al

in IET Systems Biology (2009), 3(4), 255-65

The activation of caspases is a central mechanism in apoptosis. To gain further insights into complex processes like this, mathematical modelling using ordinary differential equations (ODEs) can be a very ... [more ▼]

The activation of caspases is a central mechanism in apoptosis. To gain further insights into complex processes like this, mathematical modelling using ordinary differential equations (ODEs) can be a very powerful research tool. Unfortunately, the lack of measurement data is a common problem in building such kinetic models, because it practically constrains the identifiability of the model parameters. An existing mathematical model of caspase activation during apoptosis was used in order to design future experimental setups that will help to maximise the obtained information. For this purpose, artificial measurement data are generated in silico to simulate potential experiments, and the model is fitted to this data. The model is also analysed using observability gramian and sensitivity analyses. The used analysis methods are compared. The artificial data approach allows one to make conclusions about system properties, identifiability of parameters and the potential information content of additional measurements for the used caspase activation model. The latter facilitates to improve the experimental design of further measurements significantly. The performed analyses reveal that several kinetic parameters are not at all, or only scarcely, identifiable, and that measurements of activated caspase 8 will maximally improve the parameter estimates. Furthermore, we can show that many assays with inhibitor of apoptosis protein (IAP) knockout cells only provide redundant information for our needs and as such do not have to be carried out. [less ▲]

Detailed reference viewed: 85 (0 UL)