Summary
When stimulated by chemoattractants, eukaryotic cells respond through a combination of temporal and spatial dynamics. These responses come about because of the interaction of a large number of signaling components. The complexity of these systems makes it hard to understand without a means of systematically generating and testing hypotheses. Computer simulations have proved to be useful in testing conceptual models. Here we outline the steps required to develop these models.
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References
Ingolia, N. T. and Murray, A. W. (2004) The ups and downs of modeling the cell cycle. Curr. Biol. 14, R771–R777.
Tindall, M. J., Porter, S. L., Maini, P. K., Gaglia, G., and Armitage, J. P. (2008) Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell. Bull. Math. Biol. 70, 1525–1569.
Macnab, R. M. and Koshland, D. E., Jr. (1972) The gradient-sensing mechanism in bacterial chemotaxis. Proc. Natl. Acad. Sci. U.S.A. 69, 2509–2512.
Koshland, D. E., Jr. (1977) A response regulator model in a simple sensory system. Science 196, 1055–1063.
Barkai, N. and Leibler, S. (1997) Robustness in simple biochemical networks. Nature 387, 913–917.
Alon, U., Surette, M. G., Barkai, N., and Leibler, S. (1999) Robustness in bacterial chemotaxis. Nature 397, 168–171.
Bray, D., Levin, M. D., and Morton-Firth, C. J. (1998) Receptor clustering as a cellular mechanism to control sensitivity. Nature 393, 85–88.
Bray, D. and Duke, T. (2004) Conformational spread: the propagation of allosteric states in large multiprotein complexes. Annu. Rev. Biophys. Biomol. Struct. 33, 53–73.
Iglesias, P. A. and Devreotes, P. N. (2008) Navigating through models of chemotaxis. Curr. Opin. Cell Biol. 20, 35–40.
Janetopoulos, C., Ma, L., Devreotes, P. N., and Iglesias, P. A. (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, H. M., and Van Haastert, P. J. (2004) Chemotaxis: signalling modules join hands at front and tail. EMBO Rep. 5, 35–40.
Ma, L., Janetopoulos, C., Yang, L., Devreotes, P. N., and Iglesias, P. A. (2004) Two complementary, local excitation, global inhibition mechanisms acting in parallel can explain the chemoattractant-induced regulation of PI(3,4,5)P3 response in Dictyostelium cells. Biophys. J. 87, 3764–3774.
Alves, R., Antunes, F., and 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.
Slepchenko, B. M., Schaff, J. C., Macara, I., and Loew, L. M. (2003) Quantitative cell biology with the Virtual Cell. Trends Cell Biol. 13, 570–576.
Holmes, R. M. (2007) A Cell Biologist’s Guide to Modeling and Bioinformatics. Wiley-Interscience, Hoboken, NJ.
Li, H. Y., Ng, W. P., Wong, C. H., Iglesias, P. A., and Zheng, Y. (2007) Coordination of chromosome alignment and mitotic progression by the chromosome-based Ran signal. Cell Cycle 6, 1886–1895.
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Yang, L., Iglesias, P.A. (2009). Modeling Spatial and Temporal Dynamics of Chemotactic Networks. In: Jin, T., Hereld, D. (eds) Chemotaxis. Methods in Molecular Biology™, vol 571. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-198-1_32
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DOI: https://doi.org/10.1007/978-1-60761-198-1_32
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Publisher Name: Humana Press, Totowa, NJ
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Online ISBN: 978-1-60761-198-1
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