A two-phase growth strategy in cultured neuronal networks as reflected by the distribution of neurite branching angles.
Neurite outgrowth and branching patterns are instrumental in dictating the wiring diagram of developing neuronal networks. We study the self-organization of single cultured neurons into complex networks focusing on factors governing the branching of a neurite into its daughter branches. Neurite branching angles of insect ganglion neurons in vitro were comparatively measured in two neuronal categories: neurons in dense cultures that bifurcated under the presence of extrinsic (cellular environment) cues versus neurons in practical isolation that developed their neurites following predominantly intrinsic cues. Our experimental results were complemented by theoretical modeling and computer simulations. A preferred regime of branching angles was found in isolated neurons. A model based on biophysical constraints predicted a preferred bifurcation angle that was consistent with this range shown by our real neurons. In order to examine the origin of the preferred regime of angles we constructed simulations of neurite outgrowth in a developing network and compared the simulated developing neurons with our experimental results. We tested cost functions for neuronal growth that would be optimized at a specific regime of angles. Our results suggest two phases in the process of neuronal development. In the first, reflected by our isolated neurons, neurons are tuned to make first contact with a target cell as soon as possible, to minimize the time of growth. After contact is made, that is, after neuronal interconnections are formed, a second branching strategy is adopted, favoring higher efficiency in neurite length and volume. The two-phase development theory is discussed in relation to previous results.
Shefi
Orit
O
Department of Zoology, Tel-Aviv University, Tel-Aviv 69978, Israel.
Golebowicz
Sharon
S
Ben-Jacob
Eshel
E
Ayali
Amir
A
D000818:Animals; D001703:Biophysics / Q000379:methods; D002478:Cells, Cultured; D003198:Computer Simulation; D017952:Ganglia, Invertebrate / Q000166:cytology; D006110:Grasshoppers; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016501:Neurites / Q000502:physiology*; D009474:Neurons / Q000166:cytology*; D011336:Probability; D013997:Time Factors