An alternative stochastic model of generation of oligodendrocytes in cell culture.
According to our previous model, oligodendrocyte--type 2 (O-2A) astrocyte progenitor cells become competent for differentiation in vitro after they complete a certain number of critical mitotic cycles. After attaining the competency to differentiate, progenitor cells divide with fixed probability p in subsequent cycles. The number of critical cycles is random; analysis of data suggests that it varies from zero to two. The present paper presents an alternative model in which there are no critical cycles, and the probability that a progenitor cell will divide again decreases gradually to a plateau value as the number of completed mitotic cycles increases. In particular all progenitor cells have the ability to differentiate from the time of plating. The Kiefer-Wolfowitz procedure is used to fit the new model to experimental data on the clonal growth of purified O-2A progenitor cells obtained from the optic nerves of 7 day old rats. The new model is shown to fit the experimental data well, indicating that it is not possible to determine whether critical cycles exist on the basis of these experimental data. In contrast to the fit of the previous model, which suggested that the addition of thyroid hormone increased the limiting probability of differentiation as the number of mitotic cycles increases, the fit of the new model suggests that the addition of thyroid hormone has almost no effect on the limiting probability of differentiation.
Huntsman Cancer Institute, Department of Oncological Sciences, University of Utah, Salt Lake City 84112, USA. ken.boucher@hci.utah.edu
K
K
Boucher
A
A
Zorin
A Y
AY
Yakovlev
M
M
Mayer-Proschel
M
M
Noble
D000818:Animals; D018929:Cell Culture Techniques; D002453:Cell Cycle / Q000502:physiology; D002454:Cell Differentiation / Q000502:physiology; D002999:Clone Cells; D003198:Computer Simulation; D008954:Models, Biological; D009836:Oligodendroglia / Q000166:cytology*; D009900:Optic Nerve / Q000166:cytology; D011336:Probability; D051381:Rats; D013269:Stochastic Processes