Abstract
The study of chemotaxis has benefited greatly from computational models that describe the response of cells to chemoattractant stimuli. These models must keep track of spatially and temporally varying distributions of numerous intracellular species. Moreover, recent evidence suggests that these are not deterministic interactions, but also include the effect of stochastic variations that trigger an excitable network. In this chapter we illustrate how to create simulations of excitable networks using the Virtual Cell modeling environment.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Levchenko A, Iglesias PA (2002) Models of eukaryotic gradient sensing: application to chemotaxis of amoebae and neutrophils. Biophys J 82:50–63
Levine H, Kessler DA, Rappel WJ (2006) Directional sensing in eukaryotic chemotaxis: a balanced inactivation model. Proc Natl Acad Sci U S A 103:9761–9766
Onsum MD, Rao CV (2009) Calling heads from tails: the role of mathematical modeling in understanding cell polarization. Curr Opin Cell Biol 21:74–81
Jilkine A, Edelstein-Keshet L (2011) A comparison of mathematical models for polarization of single eukaryotic cells in response to guided cues. PLoS Comput Biol 7:e1001121
Yang L, Effler JC, Kutscher BL et al (2008) Modeling cellular deformations using the level set formalism. BMC Syst Biol 2:68
Wolgemuth CW, Stajic J, Mogilner A (2011) Redundant mechanisms for stable cell locomotion revealed by minimal models. Biophys J 101:545–553
Vanderlei B, Feng JJ, Edelstein-Keshet L (2011) A computational model of cell polarization and motility coupling mechanics and biochemistry. Multiscale Model Simul 9:1420–1443
Neilson MP, Veltman DM, van Haastert PJ et al (2011) Chemotaxis: a feedback-based computational model robustly predicts multiple aspects of real cell behaviour. PLoS Biol 9:e1000618
Hecht I, Skoge ML, Charest PG et al (2011) Activated membrane patches guide chemotactic cell motility. PLoS Comput Biol 7:e1002044
Holmes WR, Edelstein-Keshet L (2012) A comparison of computational models for eukaryotic cell shape and motility. PLoS Comput Biol 8:e1002793
Shi C, Huang CH, Devreotes PN, Iglesias PA (2013) Interaction of motility, directional sensing, and polarity modules recreates the behaviors of chemotaxing cells. PLoS Comput Biol 9:e1003122
Naoki H, Sakumura Y, Ishii S (2008) Stochastic control of spontaneous signal generation for gradient sensing in chemotaxis. J Theor Biol 255:259–266
Xiong Y, Huang CH, Iglesias PA, Devreotes PN (2010) Cells navigate with a local-excitation, global-inhibition-biased excitable network. Proc Natl Acad Sci U S A 107:17079–17086
Iglesias PA, Devreotes PN (2012) Biased excitable networks: how cells direct motion in response to gradients. Curr Opin Cell Biol 24:245–253
Ryan GL, Petroccia HM, Watanabe N, Vavylonis D (2012) Excitable actin dynamics in lamellipodial protrusion and retraction. Biophys J 102:1493–1502
Cooper RM, Wingreen NS, Cox EC (2012) An excitable cortex and memory model successfully predicts new pseudopod dynamics. PLoS One 7:e33528
Huang CH, Tang M, Shi C et al (2013) An excitable signal integrator couples to an idling cytoskeletal oscillator to drive cell migration. Nat Cell Biol 15:1307–1316
Nishikawa M, Hörning M, Ueda M, Shibata T (2014) Excitable signal transduction induces both spontaneous and directional cell asymmetries in the phosphatidylinositol lipid signaling system for eukaryotic chemotaxis. Biophys J 106:723–734
Tang M, Wang M, Shi C et al (2014) Evolutionarily conserved coupling of adaptive and excitable networks mediates eukaryotic chemotaxis. Nat Commun 5:5175
Skoge M, Yue H, Erickstad M et al (2014) Cellular memory in eukaryotic chemotaxis. Proc Natl Acad Sci U S A 111:14448–14453
Janetopoulos C, Ma L, Devreotes PN, Iglesias PA (2004) Chemoattractant-induced phosphatidylinositol 3,4,5-trisphosphate accumulation is spatially amplified and adapts, independent of the actin cytoskeleton. Proc Natl Acad Sci U S A 101:8951–8956
Postma M, Bosgraaf L, Loovers HM, Van Haastert PJ (2004) Chemotaxis: signalling modules join hands at front and tail. EMBO Rep 5:35–40
Balázsi G, van Oudenaarden A, Collins JJ (2011) Cellular decision making and biological noise: from microbes to mammals. Cell 144:910–925
Eldar A, Elowitz MB (2010) Functional roles for noise in genetic circuits. Nature 467:167–173
Rao CV, Wolf DM, Arkin AP (2002) Control, exploitation and tolerance of intracellular noise. Nature 420:231–237
Gillespie DT (2007) Stochastic simulation of chemical kinetics. Annu Rev Phys Chem 58:35–55
Munsky B, Khammash M (2006) The finite state projection algorithm for the solution of the chemical master equation. J Chem Phys 124:044104
Gillespie DT (2000) The chemical Langevin equation. J Chem Phys 113:297–306
Andrews SS (2012) Spatial and stochastic cellular modeling with the Smoldyn simulator. Methods Mol Biol 804:519–542
Andrews SS, Addy NJ, Brent R, Arkin AP (2010) Detailed simulations of cell biology with Smoldyn 2.1. PLoS Comput Biol 6:e1000705
Alves R, Antunes F, Salvador A (2006) Tools for kinetic modeling of biochemical networks. Nat Biotechnol 24:667–672
Bathe K-J (1996) Finite element procedures. Prentice Hall, Englewood Cliffs, NJ
Cowan AE, Moraru II, Schaff JC et al (2012) Spatial modeling of cell signaling networks. Methods Cell Biol 110:195–221
Resasco DC, Gao F, Morgan F et al (2012) Virtual Cell: computational tools for modeling in cell biology. Wiley Interdiscip Rev Syst Biol Med 4:129–140
Yang L, Iglesias PA (2009) Modeling spatial and temporal dynamics of chemotactic networks. Methods Mol Biol 571:489–505
Li HY, Ng WP, Wong CH et al (2007) Coordination of chromosome alignment and mitotic progression by the chromosome-based Ran signal. Cell Cycle 6:1886–1895
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Bhattacharya, S., Iglesias, P.A. (2016). Modeling Excitable Dynamics of Chemotactic Networks. In: Jin, T., Hereld, D. (eds) Chemotaxis. Methods in Molecular Biology, vol 1407. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3480-5_27
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3480-5_27
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3478-2
Online ISBN: 978-1-4939-3480-5
eBook Packages: Springer Protocols