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Online ISSN 1751-8857 Print ISSN 1751-8849

IET Systems Biology

Volume 4, Issue 6, November 2010

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Volume 4, Issue 6

November 2010

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  • Selected papers from the Third q-bio Conference on Cellular Information Processing

    • Editorial: Selected papers from the Third q-bio Conference on Cellular Information Processing
      Shaping the response: the role of FcεRI and Syk expression levels in mast cell signalling
      • Author(s): A. Nag ; J.R. Faeder ; B. Goldstein
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 334 –347
      • DOI:  10.1049/iet-syb.2010.0006
      • Type: Article
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      • p. 334 –347 (14)
        Many receptor systems initiate cell signalling through ligand-induced receptor aggregation. For bivalent ligands binding to mono- or bivalent receptors, a plot of the equilibrium concentration of receptors in aggregates against the log of the free ligand concentration, the cross-linking curve, is symmetric and bell shaped. However, steady state cellular responses initiated through receptor cross-linking may have a different dependence on ligand concentration than the aggregated receptors that initiate and maintain these responses. The authors illustrate by considering the activation of the protein kinase Syk that rapidly occurs after high affinity receptors for IgE, FcεRI, are aggregated on the surface of mast cells and basophils. Using a mathematical model of Syk activation the authors investigate two effects, one straightforward and one less so, that result in Syk activation not qualitatively following the cross-linking curve. Model predictions show that if the mechanism by which Syk is fully activated involves the transphosphorylation of Syk by Syk, then Syk activation curves can be either bell shaped or double humped, depending on the cellular concentrations of Syk and FcεRI. The model also predicts that the Syk activation curve can be non-symmetric with respect to the ligand concentration. The cell can exhibit differential Syk activation at two different ligand concentrations that produce identical distributions of receptor aggregates that form and dissociate at the same rates. The authors discuss how, even though it is only receptor aggregates that trigger responses, differences in total ligand concentration can lead to subtle kinetic effects that yield qualitative differences in the levels of Syk activation.
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      Spatial gradients in kinase cascade regulation
      • Author(s): B. Kazmierczak  and  T. Lipniacki
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 348 –355
      • DOI:  10.1049/iet-syb.2010.0002
      • Type: Article
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      • p. 348 –355 (8)
        The spatiotemporal kinetics of proteins and other substrates regulate cell fate and signaling. In this study, we consider a reaction–diffusion model of interaction of membrane receptors with a two-step kinase cascade. The receptors activate the ‘up-stream’ kinase, which may diffuse over cell volume and activate the ‘down-stream’ kinase, which is also diffusing. Both kinase species and receptors are inactivated by uniformly distributed phosphatases. The positive feedback, key to the considered dynamics, arises since the up-stream kinase activates the receptors. Such a mutual interaction is characteristic for immune cell receptors. Based on the proposed model, we demonstrated that cell sensitivity (measured as a critical value of phosphatase activity at which cell maybe activated) increases with decreasing motility of receptor-interacting kinases and with increasing polarity of receptors distribution. These two effects are cooperating, the effect of receptors localisation close to one pole of the cell grows with the decreasing kinase diffusion and vanishes in the infinite diffusion limit. As the cell sensitivity increases with decreasing diffusion of receptor-interacting kinase, the overall activity of the down-stream kinase increases with its diffusion. In conclusion, the analysis of the proposed model shows that, for the fixed substrate interaction rates, spatial distribution of the surface receptors together with the motility of intracellular kinases control cell signalling and sensitivity to extracellular signals. The increase of the cell sensitivity can be achieved by (i) localisation of receptors in a small subdomain of the cell membrane, (ii) lowering the motility of receptor-interacting kinase, (iii) increasing the motility of down-stream kinases which distribute the signal over the whole cell.
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      Identification from stochastic cell-to-cell variation: a genetic switch case study
      • Author(s): B. Munsky  and  M. Khammash
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 356 –366
      • DOI:  10.1049/iet-syb.2010.0013
      • Type: Article
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      • p. 356 –366 (11)
        Owing to the inherently random and discrete nature of genes, RNAs and proteins within living cells, there can be a wide range of variability both over time in a single cell and from cell to cell in a population of genetically identical cells. Different mechanisms and reaction rates help shape this variability in different ways, and the resulting cell-to-cell variability can be quantitatively measured using techniques such as time-lapse microscopy and fluorescence activated cell sorting (or flow cytometry). It has been shown that these measurements can help to constrain the parameters and mechanisms of stochastic gene regulatory models. In this work, finite state projection approaches are used to explore the possibility of identifying the parameters of a specific stochastic model for the genetic toggle switch consisting of mutually inhibiting proteins: LacI and λcI. This article explores the possibility of identifying the model parameters from different types of statistical information, such as mean expression levels, LacI protein distributions and LacI-λcI multivariate distributions. It is determined that although the toggle model parameters cannot be uniquely identified from measurements that track just the LacI variability, the parameters could be identified from measurements of the cell-to-cell variability in both regulatory proteins. Based upon the simulated data and the computational investigations of this study, experiments are proposed that could enable this identification.
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      Cell-penetrating peptides, electroporation and drug delivery
      • Author(s): K. Cahill
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 367 –378
      • DOI:  10.1049/iet-syb.2010.0007
      • Type: Article
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      • p. 367 –378 (12)
        Certain short polycations, such as trans-activating transcriptional activator and oligoarginine, rapidly pass through the plasma membranes of mammalian cells by a mechanism called transduction, as well as by endocytosis and macropinocytosis. These cell-penetrating peptides can carry with them cargos of 30 amino acids, more than the nominal limit of 500 Da and enough to be therapeutic. An analysis of the electrostatics of a charge outside the cell membrane and some recent experiments suggest that transduction may proceed by molecular electroporation. Ways to target diseased cells, rather than all cells, are discussed.
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      Defining cooperativity in gene regulation locally through intrinsic noise
      • Author(s): M. Maienschein-Cline ; A. Warmflash ; A.R. Dinner
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 379 –392
      • DOI:  10.1049/iet-syb.2009.0070
      • Type: Article
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      • p. 379 –392 (14)
        Regulatory networks in cells may comprise a variety of types of molecular interactions. The most basic are pairwise interactions, in which one species controls the behaviour of another (e.g. a transcription factor activates or represses a gene). Higher-order interactions, while more subtle, may be important for determining the function of networks. Here, the authors systematically expand a simple master equation model for a gene to derive an approach for robustly assessing the cooperativity (effective copy number) with which a transcription factor acts. The essential idea is that moments of a joint distribution of protein copy numbers determine the Hill coefficient of a cis-regulatory input function without non-linear fitting. The authors show that this method prescribes a definition of cooperativity that is meaningful even in highly complex situations in which the regulation does not conform to a simple Hill function. To illustrate the utility of the method, the authors measure the cooperativity of the transcription factor CI in simulations of phage-λ and show how the cooperativity accurately reflects the behaviour of the system. The authors numerically assess the effects of deviations from ideality, as well as possible sources of error. The relationship to other definitions of cooperativity and issues for experimentally realising the procedure are discussed.
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      Thermodynamic models of combinatorial gene regulation by distant enhancers
      • Author(s): J. Narula  and  O.A. Igoshin
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 393 –408
      • DOI:  10.1049/iet-syb.2010.0010
      • Type: Article
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      • p. 393 –408 (16)
        The dynamical properties of distal and proximal gene regulatory elements are crucial to their functionality in gene regulatory networks. However, the multiplicity of regulatory interactions at control elements makes their theoretical and experimental characterisation difficult. Here a thermodynamic framework to describe gene regulation by distant enhancers via a chromatin mechanism is developed. In this mechanism transcription factors (TFs) modulate gene expression via shifts in the equilibrium between chromatin states. The designs of AND, OR, XOR and NAND two-input transcriptional gates for the chromatin mechanism are proposed and compared to similar gates based on the direct physical interactions of TFs with the transcriptional machinery. An algorithm is developed to estimate the thermodynamic parameters of chromatin mechanism gates from gene expression reporter data and applied to characterise the response function for the Gata2-3 enhancer in hematopoietic stem cells. In addition waiting-time distributions for transcriptionally active states were analysed to expose the biophysical differences between the contact and chromatin mechanisms. These differences can be experimentally observed in single-cell experiments and therefore can serve as a signature of the gene regulation mechanism. Taken together these results indicate the diverse functionality and unique features of the chromatin mechanism of combinatorial gene regulation. [Includes supplementary material]
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      Time-dependent corrections to effective rate and event statistics in Michaelis–Menten kinetics
      • Author(s): N.A. Sinitsyn  and  I. Nemenman
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 409 –415
      • DOI:  10.1049/iet-syb.2010.0064
      • Type: Article
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      • p. 409 –415 (7)
        The authors generalise the concept of the geometric phase in stochastic kinetics to a non-cyclic evolution. Its application is demonstrated on kinetics of the Michaelis–Menten reaction. It is shown that the non-periodic geometric phase is responsible for the correction to the Michaelis–Menten law when parameters, such as a substrate concentration, are changing with time. The authors apply these ideas to a model of chemical reactions in a bacterial culture of a growing size, where the geometric correction qualitatively changes the outcome of the reaction kinetics.
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      Towards monitoring real-time cellular response using an integrated microfluidics-matrix assisted laser desorption ionisation/nanoelectrospray ionisation-ion mobility-mass spectrometry platform
      • Author(s): J.R. Enders ; C.C. Marasco ; A. Kole ; B. Nguyen ; S. Sevugarajan ; K.T. Seale ; J.P. Wikswo ; J.A. McLean
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 416 –427
      • DOI:  10.1049/iet-syb.2010.0012
      • Type: Article
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      • p. 416 –427 (12)
        The combination of microfluidic cell trapping devices with ion mobility-mass spectrometry offers the potential for elucidating in real time the dynamic responses of small populations of cells to paracrine signals, changes in metabolite levels and delivery of drugs and toxins. Preliminary experiments examining peptides in methanol and recording the interactions of yeast and Jurkat cells with their superfusate have identified instrumental set-up and control parameters and online desalting procedures. Numerous initial experiments demonstrate and validate this new instrumental platform. Future outlooks and potential applications are addressed, specifically how this instrumentation may be used for fully automated systems biology studies of the significantly interdependent, dynamic internal workings of cellular metabolic and signalling pathways.
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      Multivariate dependence and genetic networks inference
      • Author(s): A.A. Margolin ; K. Wang ; A. Califano ; I. Nemenman
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 428 –440
      • DOI:  10.1049/iet-syb.2010.0009
      • Type: Article
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      • p. 428 –440 (13)
        A critical task in systems biology is the identification of genes that interact to control cellular processes by transcriptional activation of a set of target genes. Many methods have been developed that use statistical correlations in high-throughput data sets to infer such interactions. However, cellular pathways are highly cooperative, often requiring the joint effect of many molecules. Few methods have been proposed to explicitly identify such higher-order interactions, partially due to the fact that the notion of multivariate statistical dependence itself remains imprecisely defined. The authors define the concept of dependence among multiple variables using maximum entropy techniques and introduce computational tests for their identification. Synthetic network results reveal that this procedure uncovers dependencies even in undersampled regimes, when the joint probability distribution cannot be reliably estimated. Analysis of microarray data from human B cells reveals that third-order statistics, but not second-order ones, uncover relationships between genes that interact in a pathway to cooperatively regulate a common set of targets.
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      Fast adaptive uniformisation of the chemical master equation
      • Author(s): M. Mateescu ; V. Wolf ; F. Didier ; T.A. Henzinger
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 441 –452
      • DOI:  10.1049/iet-syb.2010.0005
      • Type: Article
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      • p. 441 –452 (12)
        Within systems biology there is an increasing interest in the stochastic behaviour of biochemical reaction networks. An appropriate stochastic description is provided by the chemical master equation, which represents a continuous-time Markov chain (CTMC). The uniformisation technique is an efficient method to compute probability distributions of a CTMC if the number of states is manageable. However, the size of a CTMC that represents a biochemical reaction network is usually far beyond what is feasible. In this study, the authors present an on-the-fly variant of uniformisation, where they improve the original algorithm at the cost of a small approximation error. By means of several examples, the authors show that their approach is particularly well-suited for biochemical reaction networks.
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      Rule-based modelling and simulation of biochemical systems with molecular finite automata
      • Author(s): J. Yang ; X. Meng ; W.S. Hlavacek
      • Source: IET Systems Biology, Volume 4, Issue 6, p. 453 –466
      • DOI:  10.1049/iet-syb.2010.0015
      • Type: Article
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      • p. 453 –466 (14)
        The authors propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modelling individual protein behaviours and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein–protein interactions as synchronised machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. They apply the MFA formalism to model and simulate a simple example of a signal-transduction system that involves an MAP kinase cascade and a scaffold protein.
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