A Model for Gliding and Aggregation of Myxobacteria

  • Angela Stevens
Part of the NATO ASI Series book series (NSSB, volume 244)


In morphogenesis, cells recognize and find each other to build complex structures. Up to now, the mechanism for this phenomenon is not fully understood. Because of their cooperative gliding and aggregation, the myxobacteria serve as a model problem for investigations in this direction. To get a better insight into these problems, a theoretical approach is chosen and represented in a cellular automaton model.


Fruiting Body Cell Track Cellular Automaton Model Fruiting Body Formation Aggregation Centre 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Dworkin, M. & Eide, D. (1983). Myxococcus xanthus does not respond chemotactically to moderate concentration gradients. J. Bacteriol. 154, 437–442.Google Scholar
  2. [2]
    Dworkin, M., Keller, K.H. & Weisberg, D. (1983). Experimental observations consistent with surface tension model of gliding motility of Myxococcus xanthus. J. Bacteriol. 155, 1367–1371.Google Scholar
  3. [3]
    Hodgekin, J. & Kaiser, D. (1979). Genetics of gliding motility in Myxococcus xanthus (Myxobacterales): two gene systems control movement. Mol. Gen. Genet. 171, 177–191.CrossRefGoogle Scholar
  4. [4]
    Keller, K.H., Grady, M. & Dworkin, M. (1983). Surface tension gradients: Feasible models for gliding motility in Myxococcus xanthus. J. Bacteriol. 155, 1358–1366.Google Scholar
  5. [5]
    Kuner, J.M. & Kaiser, D. (1982). Fruiting body morphogenesis in submerged cultures of Myxococcus xanthus. J. Bacteriol. 151, 458–461.Google Scholar
  6. [6]
    Lauffenburger, D. (1984). An hypothesis for approaching swarms of Myxobacteria. J. Theor. Biol. 110, 257–274.CrossRefGoogle Scholar
  7. [7]
    Oelschlager, K. (1987). A fluctuation theorem for moderately interacting diffusion processes. Probab. Th. Rel. Fields 74, 591–616.CrossRefMathSciNetGoogle Scholar
  8. [8]
    Oelschlager, K. On the derivation of reaction-diffusion equations as limit dynamics of systems of moderately interacting stochastic processes. To appear in Probab. Th. Rel. Fields.Google Scholar
  9. [9]
    Reichenbach, H. (1965). Rhythmische Vorgange bei der Schwarmentfaltung von Myxobakterien. Berichte der Deutschen Botanischen Gesellschaft 78, 102–105.Google Scholar
  10. [10]
    Reichenbach, H. (1965). Untersuchungen an Archangium violaceum. Ein Beitrag zur Kenntnis der Myxobakterien. Berichte der Deutschen Botanischen Gesellschaft. Arch. Microbiol. 52, 376–403.Google Scholar
  11. [11]
    Reichenbach, H. (1986). The myxobacteria: common organisms with uncommon behaviour. Microbiol. Sc.3 (No. 9), 268–274.Google Scholar
  12. [12]
    Shimkets, L.J. & Dworkin, M. (1981). Excreted adenosine is a cell density signal for the initiation of fruiting body formation in Myxococcus xanthus. Dev. Biol. 84, 51–60.CrossRefGoogle Scholar
  13. [13]
    Stanier, R.Y. (1942). A note on elasticotaxis in myxobacteria. J. Bacteriol. 44, 405–412.Google Scholar
  14. [14]
    Stevens, A. (1990). Simulations of the aggregation and gliding behaviour of myxobacteria. To appear in Lecture Notes in Biomathematics.Google Scholar
  15. [15]
    White, D. (1987). Cell interactions and the control of development in myxobacteria populations. Int. Rev. Cytol. 71, 203–227.Google Scholar

Copyright information

© Springer Science+Business Media New York 1991

Authors and Affiliations

  • Angela Stevens
    • 1
  1. 1.SFB 123Institut für Angewandte MathematikHeidelbergGermany

Personalised recommendations