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Online ISSN 1751-8857 Print ISSN 1751-8849

IET Systems Biology

Volume 5, Issue 3, May 2011

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Volume 5, Issue 3

May 2011

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    • Critical perspective on the consequences of the limited availability of kinetic data in metabolic dynamic modelling
      • Author(s): R.S. Costa ; D. Machado ; I. Rocha ; E.C. Ferreira
      • Source: IET Systems Biology, Volume 5, Issue 3, p. 157 –163
      • DOI:  10.1049/iet-syb.2009.0058
      • Type: Article
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      • p. 157 –163 (7)
        Detailed kinetic models at the network reaction level are usually constructed using enzymatic mechanistic rate equations and the associated kinetic parameters. However, during the cellular life cycle thousands of different reactions occur, which makes it very difficult to build a detailed large-scale ldnetic model. In this work, we provide a critical overview of specific limitations found during the reconstruction of the central carbon metabolism dynamic model from E. coli (based on kinetic data available). In addition, we provide clues that will hopefully allow the systems biology community to more accurately construct metabolic dynamic models in the future. The difficulties faced during the construction of dynamic models are due not only to the lack of kinetic information but also to the fact that some data are still not curated. We hope that in the future, with the standardization of the in vitro enzyme protocols the approximation of in vitro conditions to the in vivo ones, it will be possible to integrate the available kinetic data into a complete large scale model. We also expect that collaborative projects between modellers and biologists will provide valuable kinetic data and permit the exchange of important information to solve most of these issues.
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      Cell population modelling describes intrinsic heterogeneity: a case study for hematopoietic stem cells
      • Author(s): C. Luni ; F.J. Doyle ; N. Elvassore
      • Source: IET Systems Biology, Volume 5, Issue 3, p. 164 –173
      • DOI:  10.1049/iet-syb.2009.0059
      • Type: Article
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      • p. 164 –173 (10)
        The control of stem cell properties during in vitro expansion is of paramount importance for their clinical use. According to Food and Drug Administration (FDA) guidelines, phenotypic heterogeneity is a critical aspect influencing therapeutic response. Even if the authors ability to reduce heterogeneity were limited, the sources from which it arises should be well understood for safe clinical applications. The aim of this work was to describe theoretically the intrinsic cell population heterogeneity that is present even when cells are cultured in a perfectly homogeneous environment. A bivariate population balance model is developed to account for the heterogeneity in the number of receptors and receptor–ligand complexes per cell, and is coupled with a ligand conservation equation. As a case study, the model is applied to the hematopoietic stem cell expansion, considering the c-Kit receptor and stem cell factor pair. Results show the dependence of intrinsic heterogeneity from ligand concentration and the kinetics of its administration. By tracking the cell generations within the total population, the authors highlight intra- and an inter-generational contributions to total population heterogeneity. In terms of dimensionless variables, intrinsic heterogeneity is dependent on the ratio of the characteristic time of cell division to that needed by a newborn cell to reach its single-cell steady state. [Includes supplementary material]
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      Exploring phospholipase C-coupled Ca2+ signalling networks using boolean modelling
      • Author(s): G. Bhardwaj ; C.P. Wells ; R. Albert ; D.B. van Rossum ; R.L. Patterson
      • Source: IET Systems Biology, Volume 5, Issue 3, p. 174 –184
      • DOI:  10.1049/iet-syb.2010.0019
      • Type: Article
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      • p. 174 –184 (11)
        In this study, the authors explored the utility of a descriptive and predictive bionetwork model for phospholipase C-coupled calcium signalling pathways, built with non-kinetic experimental information. Boolean models generated from these data yield oscillatory activity patterns for both the endoplasmic reticulum resident inositol-1,4,5-trisphosphate receptor (IP3R) and the plasma-membrane resident canonical transient receptor potential channel 3 (TRPC3). These results are specific as randomisation of the Boolean operators ablates oscillatory pattern formation. Furthermore, knock-out simulations of the IP3R, TRPC3 and multiple other proteins recapitulate experimentally derived results. The potential of this approach can be observed by its ability to predict previously undescribed cellular phenotypes using in vitro experimental data. Indeed, our cellular analysis of the developmental and calcium-regulatory protein, DANGER1a, confirms the counter-intuitive predictions from our Boolean models in two highly relevant cellular models. Based on these results, the authors theorise that with sufficient legacy knowledge and/or computational biology predictions, Boolean networks can provide a robust method for predictive modelling of any biological system. [Includes supplementary material]
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      Networks for systems biology: conceptual connection of data and function
      • Author(s): F. Emmert-Streib  and  M. Dehmer
      • Source: IET Systems Biology, Volume 5, Issue 3, p. 185 –207
      • DOI:  10.1049/iet-syb.2010.0025
      • Type: Article
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      • p. 185 –207 (23)
        The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.
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      Effects of saturation and enzyme limitation in feedforward adaptive signal transduction
      • Author(s): J. Krishnan
      • Source: IET Systems Biology, Volume 5, Issue 3, p. 208 –219
      • DOI:  10.1049/iet-syb.2010.0048
      • Type: Article
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      • p. 208 –219 (12)
        In this study, the author examines the effects of saturation and enzyme limitation in temporal and spatial signal transduction in a generic feedforward adaptive module. The feedforward module encompasses a range of temporal and spatial signal processing, and this study systematically examines the effect of enzyme limitation/saturating effects in each of the feedforward pathways, and their interplay. It is found that this saturation makes the adaptation inexact, and this effect is more pronounced for higher levels of input signals. Further, it has a very significant role in affecting the temporal dynamics of this module. In examining the role of saturation in the module response to static gradients, the author finds that in certain cases, saturation can completely alter the gradient response. The author examines various aspects of the response systematically using analytical methods and simulations. Overall the author studies a framework and basis for examining and understanding the roles of saturating effects in multiple pathways involved in adaptive responses and sheds light on the relationship and connection between exact and inexact adaptation.
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      Mathematical modelling of negative feedback regulation by carboxyltransferase
      • Author(s): G. Meades ; X. Cai ; N.K. Thalji ; G.L. Waldrop ; M. de Queiroz
      • Source: IET Systems Biology, Volume 5, Issue 3, p. 220 –228
      • DOI:  10.1049/iet-syb.2010.0071
      • Type: Article
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      • p. 220 –228 (9)
        Acetyl-CoA carboxylase catalyses the first committed step in fatty acid synthesis in all organisms. The chemistry is accomplished in two half-reactions: activation of biotin via carboxylation by biotin carboxylase, followed by the carboxyltransferase-catalysed transfer of the carboxyl moiety from carboxybiotin to acetyl-CoA to generate malonyl-CoA. The Escherichia coli form of the carboxyltransferase subunit was recently found to regulate its own activity and expression by binding its own mRNA. By binding acetyl-CoA or the mRNA encoding its own subunits, carboxyltransferase is able to sense the metabolic state of the cell and attenuate its own translation and enzymatic activity using a negative feedback mechanism. Here, the network of these interactions is modelled mathematically with a set of non-linear differential equations. Numerical simulations of the model show that it qualitatively and quantitatively agrees with the experimental results for both inhibition of carboxyltransferase by mRNA and attenuation of translation. The modelling of the autoregulatory function of carboxyltransferase confirms that it is more than isolated interactions, but functions as a single dynamic system.
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