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Jacky L Snoep

Publications and source records attributed to Jacky L Snoep.

At least 19 recordsLinked to original sources
PubMed2006

BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems.

BioModels Database (http://www.ebi.ac.uk/biomodels/), part of the international initiative BioModels.net, provides access to published, peer-reviewed, quantitative models of biochemical and cellular systems. Each model is carefully curated to verify that it corresponds to the reference publication and gives the proper numerical results. Curators also annotate the components of the models with terms from controlled vocabularies and links to other relevant data resources. This allows the users to search accurately for the models they need. The models can currently be retrieved in the SBML format, and import/export facilities are being developed to extend the spectrum of formats supported by the resource.

Biochemical Phenomena↗
PubMed2005

Towards building the silicon cell: a modular approach.

Systems Biology aims to understand quantitatively how properties of biological systems can be understood as functions of the characteristics of, and interactions between their macromolecular components. Whereas, traditional biochemistry focused on isolation and characterization of cellular components, the challenge for Systems Biology lies in integration of this knowledge and the knowledge about molecular interactions. Computer models play an important role in this integration. We here discuss an approach with which we aim to link kinetic models on small parts of metabolism together, so as to form detailed kinetic models of larger chunks of metabolism, and ultimately of the entire living cell. Specifically, we will discuss techniques that can be used to model a sub-network in isolation of a larger network of which it is a part, while still maintaining the dynamics of the larger complete network. We will start by outlining the JWS online system, the silicon cell project, and the type of models we propose. JWS online is a model repository, which can be used for the storage, simulation and analysis of kinetic models. We advocate to integrate a top-down approach, where measurements on the complete system are used to derive fluxes in a detailed structural model, with a bottom-up approach, consisting of the integration of molecular mechanism-based detailed kinetic models into the structural model.

Animals↗
PubMed2005

Yeast glycolytic oscillations that are not controlled by a single oscillophore: a new definition of oscillophore strength.

Biochemical oscillations, such as glycolytic oscillations, are often believed to be caused by a single so-called 'oscillophore'. The main characteristics of yeast glycolytic oscillations, such as frequency and amplitude, are however controlled by several enzymes. In this paper, we develop a method to quantify to which extent any enzyme determines the occurrence of oscillations. Principles extrapolated from metabolic control analysis are applied to calculate the control exerted by individual enzymes on the real and imaginary parts of the eigenvalues of the Jacobian matrix. We propose that the control exerted by an enzyme on the real part of the smallest eigenvalue, in terms of absolute value, quantifies to which extent that enzyme contributes to the emergence of instability. Likewise the control exerted by an enzyme on the imaginary part of complex eigenvalues may serve to quantify the extent to which that enzyme contributes to the tendency of the system to oscillate. The method was applied both to a core model and to a realistic model of yeast glycolytic oscillations. Both the control over stability and the control over oscillatory tendency were distributed among several enzymes, of which glucose transport, pyruvate decarboxylase and ATP utilization were the most important. The distributions of control were different for stability and oscillatory tendency, showing that control of instability does not imply control of oscillatory tendency nor vice versa. The control coefficients summed up to 1, suggesting the existence of a new summation theorem. These results constitute proof that glycolytic oscillations in yeast are not caused by a single oscillophore and provide a new, subtle, definition for the oscillophore strength of an enzyme.

Biological Clocks↗
PubMed2005

The Silicon Cell initiative: working towards a detailed kinetic description at the cellular level.

The Silicon Cell initiative aims to understand cellular systems on the basis of the characteristics of their components. As a tool to achieve this, detailed kinetic models at the network reaction level are being constructed. Such detailed kinetic models are extremely useful for medical and biotechnological applications and form strong tools for fundamental studies. Several recently constructed detailed kinetic models on metabolism (glycolysis), signal transduction (EGF receptor), and the eukaryotic cell cycle (Saccharomyces cerevisiae) have been used to exemplify the Silicon Cell project. These models are stored and made accessible via the JWS Online Cellular Systems Modeling project, a web-based repository of kinetic models. Using a web-browser the models can be interrogated via a user-friendly graphical interface. The goal of the two projects is to combine models on parts of cellular systems and ultimately to construct detailed kinetic models at the cellular level.

Carbon↗
PubMed2005

Minimum information requested in the annotation of biochemical models (MIRIAM).

Most of the published quantitative models in biology are lost for the community because they are either not made available or they are insufficiently characterized to allow them to be reused. The lack of a standard description format, lack of stringent reviewing and authors' carelessness are the main causes for incomplete model descriptions. With today's increased interest in detailed biochemical models, it is necessary to define a minimum quality standard for the encoding of those models. We propose a set of rules for curating quantitative models of biological systems. These rules define procedures for encoding and annotating models represented in machine-readable form. We believe their application will enable users to (i) have confidence that curated models are an accurate reflection of their associated reference descriptions, (ii) search collections of curated models with precision, (iii) quickly identify the biological phenomena that a given curated model or model constituent represents and (iv) facilitate model reuse and composition into large subcellular models.

Biochemistry↗
PubMed2004

An ffh mutant of Streptococcus mutans is viable and able to physiologically adapt to low pH in continuous culture.

Previously, we described in Streptococcus mutans strain NG8 a 5-gene operon (sat) that includes ffh, the bacterial homologue of the eukaryotic signal recognition particle (SRP) protein, SR54. A mutation in ffh resulted in acid sensitivity but not loss of viability. In the present study, chemostat-grown cells of the ffh mutant were shown to possess only 26% and 39% of the parental membrane F-ATPase activity and 55% and 75% of parental glucose-phosphotransferase (PTS) activity when pH-7 and pH-5-grown cells, respectively, were assayed. Two-dimensional-gel electrophoretic analyses revealed significant differences in protein profiles between parent and ffh-mutant strains at both pH 5 and pH 7. It appears that the loss of active SRP (Ffh) function, while not lethal, results in substantial alterations in cellular physiology that includes acid tolerance.

Acclimatization↗
PubMed2004

Web-based kinetic modelling using JWS Online.

UNLABELLED: JWS Online is a repository of kinetic models, describing biological systems, which can be interactively run and interrogated over the Internet. It is implemented using a client-server strategy where the clients, in the form of web browser based Java applets, act as a graphical interface to the model servers, which perform the required numerical computations. AVAILABILITY: The JWS Online website is publicly accessible at http://jjj.biochem.sun.ac.za/ with mirrors at http://www.jjj.bio.vu.nl/ and http://jjj.vbi.vt.edu/

Cell Physiological Phenomena↗
PubMed2004

Physiological implications of class IIa bacteriocin resistance in Listeria monocytogenes strains.

High-level resistance to class IIa bacteriocins has been directly associated with the absent EIIAB(Man) (MptA) subunit of the mannose-specific phosphoenolpyruvate-dependent phosphotransferase system (PTS) (EIIt(MAN)) in Listeria monocytogenes strains. Class IIa bacteriocin-resistant strains used in this study were a spontaneous resistant, L. monocytogenes B73-MR1, and a defined mutant, L. monocytogenes EGDe-mptA. Both strains were previously reported to have the EIIAB(Man) PTS component missing. This study shows that these class IIa bacteriocin-resistant strains have significantly decreased specific growth and glucose consumption rates, but they also have a significantly higher growth yield than their corresponding wild-type strains, L. monocytogenes B73 and L. monocytogenes EGDe, respectively. In the presence of glucose, the strains showed a shift from a predominantly lactic-acid to a mixed-acid fermentation. It is here proposed that elimination of the EIIAB(Man) in the resistant strains has caused a reduced glucose consumption rate and a reduced specific growth rate. The lower glucose consumption rate can be correlated to a shift in metabolism to a more efficient pathway with respect to ATP production per glucose, leading to a higher biomass yield. Thus, the cost involved in obtaining bacteriocin resistance, i.e. losing substrate transport capacity leading to a lower growth rate, is compensated for by a higher biomass yield.

Bacteriocins↗
PubMed2004

Role of hexose transport in control of glycolytic flux in Saccharomyces cerevisiae.

The yeast Saccharomyces cerevisiae predominantly ferments glucose to ethanol at high external glucose concentrations, irrespective of the presence of oxygen. In contrast, at low external glucose concentrations and in the presence of oxygen, as in a glucose-limited chemostat, no ethanol is produced. The importance of the external glucose concentration suggests a central role for the affinity and maximal transport rates of yeast's glucose transporters in the control of ethanol production. Here we present a series of strains producing functional chimeras between the hexose transporters Hxt1 and Hxt7, each of which has distinct glucose transport characteristics. The strains display a range of decreasing glycolytic rates resulting in a proportional decrease in ethanol production. Using these strains, we show for the first time that at high glucose levels, the glucose uptake capacity of wild-type S. cerevisiae does not control glycolytic flux during exponential batch growth. In contrast, our chimeric Hxt transporters control the rate of glycolysis to a high degree. Strains whose glucose uptake is mediated by these chimeric transporters will undoubtedly provide a powerful tool with which to examine in detail the mechanism underlying the switch between fermentation and respiration in S. cerevisiae and will provide new tools for the control of industrial fermentations.

Biological Transport↗
PubMed2002

Selectivity in overlapping MAP kinase cascades.

Some protein kinases operate in more than one mitogen-activated protein-kinase (MAPK) cascade. We here address the question whether specificity of the cascades necessitates physical sequestration of these "promiscuous" kinases (e.g. by binding to scaffolds). A model is constructed, in which two MAPK cascades depend on a single MAP-kinase kinase that is not sequestered in two subpopulations. We show that in this model selective signal transduction is possible provided that there is an additional interaction at the MAP-kinase level, there is no simultaneous activation of more than one response by either signal. We discuss a number of additional interactions that can generate the selectivity, as well as some kinetic features by which this mechanism may be recognized experimentally.

Adaptation, Physiological↗
PubMed2002

Putting intentions into cell biochemistry: an artificial intelligence perspective.

The living cell exists by virtue of thousands of nonlinearly interacting processes. This complexity greatly impedes its understanding. The standard approach to the calculation of the behaviour of the living cell, or part thereof, integrates all the rate equations of the individual processes. If successful extremely intensive calculations often lead the calculation of coherent, apparently simple, cellular "decisions" taken in response to a signal: the complexity of the behavior of the cell is often smaller than it might have been. The "decisions" correspond to the activation of entire functional units of molecular processes, rather than individual ones. The limited complexity of signal and response suggests that there might be a simpler way to model at least some important aspects of cell function. In the field of Artificial Intelligence, such simpler modelling methods for complex systems have been developed. In this paper, it is shown how the Artificial Intelligence description method for deliberative agents functioning on the basis of beliefs, desires and intentions as known in Artificial Intelligence, can be used successfully to describe essential aspects of cellular regulation. This is demonstrated for catabolite repression and substrate induction phenomena in the bacterium Escherichia coli. The method becomes highly efficient when the computation is automated in a Prolog implementation. By defining in a qualitative way the food supply of the bacterium, the make-up of its catabolic pathways is readily calculated for cases that are sufficiently complex to make the traditional human reasoning tedious and error prone.

Animals↗
PubMed2002

Control analysis for autonomously oscillating biochemical networks.

It has hitherto not been possible to analyze the control of oscillatory dynamic cellular processes in other than qualitative ways. The control coefficients, used in metabolic control analyses of steady states, cannot be applied directly to dynamic systems. We here illustrate a way out of this limitation that uses Fourier transforms to convert the time domain into the stationary frequency domain, and then analyses the control of limit cycle oscillations. In addition to the already known summation theorems for frequency and amplitude, we reveal summation theorems that apply to the control of average value, waveform, and phase differences of the oscillations. The approach is made fully operational in an analysis of yeast glycolytic oscillations. It follows an experimental approach, sampling from the model output and using discrete Fourier transforms of this data set. It quantifies the control of various aspects of the oscillations by the external glucose concentration and by various internal molecular processes. We show that the control of various oscillatory properties is distributed over the system enzymes in ways that differ among those properties. The models that are described in this paper can be accessed on http://jjj.biochem.sun.ac.za.

Biochemistry↗
PubMed2002

DNA supercoiling by gyrase is linked to nucleoid compaction.

The genes of E. coli are located on a circular chromosome of 4.6 million basepairs. This 1.6 mm long molecule is compressed into a nucleoid to fit inside the 1-2 microm cell in a functional format. To examine the role of DNA supercoiling as nucleoid compaction force we modulated the activity of DNA gyrase by electronic, genetic, and chemical means. A model based on physical properties of DNA and other cell components predicts that relaxation of supercoiling expands the nucleoid. Nucleoid size did not increase after reduction of DNA gyrase activity by genetic or chemical means, but nucleoids did expand upon chemical inhibition of gyrase in chloramphenicol-treated cells, indicating that supercoiling may help to compress the genome.

DNA Gyrase↗
PubMed2002

ECA: control in ecosystems.

Although metabolic control analysis (MCA) cannot be applied directly to microbial ecological systems because of mass conservation and stoichiometric constraints, we demonstrate here that Hierarchical Control Analysis (HCA) can be applied to such systems. We illustrate the approach for a particular ecosystem example of the biological synthesis of acetic acid from glucose, and uncover some surprising aspects to the control of this miniature ecosystem.

Acetic Acid↗
PubMed2002

The extent to which ATP demand controls the glycolytic flux depends strongly on the organism and conditions for growth.

Using molecular genetics we have introduced uncoupled ATPase activity in two different bacterial species, Escherichia coli and Lactococcus lactis, and determined the elasticities of the growth rate and glycolytic flux towards the intracellular [ATP]/[ADP] ratio. During balanced growth in batch cultures of E. coli the ATP demand was found to have almost full control on the glycolytic flux (FCC=0.96) and the flux could be stimulated by 70%. In contrast to this, in L. lactis the control by ATP demand on the glycolytic flux was close to zero. However, when we used non-growing cells of L. lactis (which have a low glycolytic flux) the ATP demand had a high flux control and the flux could be stimulated more than two fold. We suggest that the extent to which ATP demand controls the glycolytic flux depends on how much excess capacity of glycolysis is present in the cells.

Adenosine Diphosphate↗
PubMed2002

Metabolic control in integrated biochemical systems.

Traditional analyses of the control and regulation of steady-state concentrations and fluxes assume the activities of the enzymes to be constant. In living cells, a hierarchical control structure connects metabolic pathways to signal-transduction and gene-expression. Consequently, enzyme activities are not generally constant. This would seem to compromise analyses of control and regulation at the metabolic level. Here, we investigate the concept of metabolic quasi-steady state kinetics as a means of applying metabolic control analysis to hierarchical biochemical systems. We discuss four methods that enable the experimental determination of metabolic control coefficients, and demonstrate these by computer simulations. The best method requires extra measurement of enzyme activities, two others are simpler but are less accurate and one method is bound only to work under special conditions. Our results may assist in evaluating the relative importance of transcriptomics and metabolomics for functional genomics.

Enzymes↗