Abstract
We develop two models for Myxobacteria swarming, a modified Lattice Gas Cellular Automata (LGCA) model and an off-lattice CA model. In the LGCA model each cell is represented by one node for the center of mass and an extended rod-shaped cell profile. Cells check the surrounding area and choose in which direction to move based on the local interactions. Using this model, we obtained a density vs. expansion rate curve with the shape similar to the experimental curve for the wild type Myxobacteria. In the off-lattice model, each cell is represented by a string of nodes. Cells can bend and move freely in the two-dimensional space. We use a phenomenological algorithm to determine the moving direction of cells guided by slime trail; the model allows for cell bending and alignment during collisions. In the swarming simulations for A+S- Myxobacteria, we demonstrate the formation of peninsula structures, in agreement with experiments.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kaiser, D., Crosby, C.: Cell movement and its coordination in swarms of Myxococcus xanthus. Cell Motility 3, 227–245 (1983)
Kaiser, D.: Coupling Cell Movement to Multicellular Development in Myxobacteria. Nature Reviews Microbiology 1, 45–54 (2003)
Sozinova, O., Jiang, Y., Kaiser, D., Alber, M.: A three-dimensional model of myxobacterial aggregation by contact-mediated interactions. Proc. Natl. Acad. Sci. U.S.A. 102, 11308–11312 (2005)
Hodgkin, J., Kaiser, D.: Genetics of gliding motility in M. xanthus (Myxobacterales): two gene systems control movement. Mol. Gen. Genet. 171, 177–191 (1979)
Wolgemuth, C., Hoiczyk, E., Kaiser, D., Oster, G.: How Myxobacteria Glide. Curr. Biol. 12, 369–377 (2002)
Kaiser, D., Yu, R.: Reversing cell polarity: evidence and hypothesis. Cur. Opin. Microbiol. 8, 216–221 (2005)
Kaiser, D.: Signaling in Myxobacteria. Annu. Rev. Microbiol. 58, 75–98 (2004)
Burchard, R.P.: Trail following by gliding bacteria. J. Bacteriol. 152, 495–501 (1982)
Gallegos, A., Mazzag, B., Mogilner, A.: Mathematical analysis of the swarming behavior of myxobacteria. Bulletin of Mathematical Biology (in print)
Hardy, J., Pazzis, O., Pomeau, Y.: Molecular dynamics of a classical lattice gas: Transport properties and time correlation functions. Phys. Rev. A 13, 1949–1961 (1976)
Palsson, E., Othmer, H.G.: A model for individual and collective cell movement in Dictyostelium discoideum. Proc. Natl. Acad. Sci. USA. 97, 10448–10453 (2000)
Spormann, A.M., Kaiser, D.: Gliding movements in Myxococcus xanthus. J. Bacteriol. 177, 5846–5852 (1995)
Newman, T.J.: Modeling Multicellular systems using subcellular elements. Mathematical Biosciences and Engineering 2, 611–622 (2005)
Newman, M.E.J., Barkema, G.T.: Monte Carlo Methods in Statistical Physics. Clarendon Press, Oxford (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, Y., Chen, N., Rissler, M., Jiang, Y., Kaiser, D., Alber, M. (2006). CA Models of Myxobacteria Swarming. In: El Yacoubi, S., Chopard, B., Bandini, S. (eds) Cellular Automata. ACRI 2006. Lecture Notes in Computer Science, vol 4173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861201_24
Download citation
DOI: https://doi.org/10.1007/11861201_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40929-8
Online ISBN: 978-3-540-40932-8
eBook Packages: Computer ScienceComputer Science (R0)