Predicting spiral wave patterns from cell properties in a model of biological self-organization.
In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.
Computational Systems Biology, School of Engineering and Science, Jacobs University, Bremen 28759, Germany. d.geberth@jacobs-university.de
Daniel
D
Geberth
Marc-Thorsten
MT
Hütt
D000465:Algorithms; D000818:Animals; D001695:Biology / Q000379:methods*; D001703:Biophysics / Q000379:methods*; D002465:Cell Movement; D002633:Chemotaxis; D003198:Computer Simulation; D000242:Cyclic AMP / Q000378:metabolism; D004023:Dictyostelium / Q000378:metabolism*; D008954:Models, Biological; D015233:Models, Statistical; D011336:Probability; D015398:Signal Transduction
D000242:Cyclic AMP