ABSTRACT
Cerebellar granule neuron progenitors (CGNPs) give rise to the cerebellar granule neurons in the developing cerebellum. Generation of large number of these neurons is made possible by the high proliferation rate of CGNPs in the external granule layer (EGL) in the dorsal cerebellum. Here, we show that upregulation of ß-catenin can maintain murine CGNPs in a state of proliferation. Further, we show that ß-catenin mRNA and protein levels can be regulated by the mitogen Sonic hedgehog (Shh). Shh signaling led to an increase in the level of the transcription factor N-myc. N-myc was found to bind the ß-catenin promoter, and the increase in ß-catenin mRNA and protein levels could be prevented by blocking N-myc upregulation downstream of Shh signaling. Furthermore, blocking Wingless-type MMTV integration site (Wnt) signaling by Wnt signaling pathway inhibitor Dickkopf 1 (Dkk-1) in the presence of Shh did not prevent the upregulation of ß-catenin. We propose that in culture, Shh signaling regulates ß-catenin expression through N-myc and results in increased CGNP proliferation.
Subject(s)
Cell Proliferation/physiology , Hedgehog Proteins/metabolism , Neural Stem Cells/metabolism , Neurons/metabolism , beta Catenin/metabolism , Animals , Cells, Cultured , Cerebellar Neoplasms/genetics , Cerebellum/metabolism , Interneurons/metabolism , Medulloblastoma/genetics , Mice, Inbred BALB C , beta Catenin/geneticsABSTRACT
Models based on surfactant-driven instabilities have been employed to describe pattern formation by swarming bacteria. However, by definition, such models cannot account for the effect of bacterial sensing and decision making. Here we present a more complete model for bacterial pattern formation which accounts for these effects by coupling active bacterial motility to the passive fluid dynamics. We experimentally identify behaviors which cannot be captured by previous models based on passive population dispersal and show that a more accurate description is provided by our model. It is seen that the coupling of bacterial motility to the fluid dynamics significantly alters the phase space of surfactant-driven pattern formation. We also show that our formalism is applicable across bacterial species.
