Coordination of vertebrate neurogenesis in space and time

Stem cells have the ability to form every cell in the body. It is for this reason that there is great hope in using them to cure a variety of diseases including neurodegenerative disorders. One of the main problems we have is how can we control this ability in a culture dish so that we only form the correct type of cells we need. The nervous system may be especially problematic because there are many different types of neurons. So the problem is not just to form neurons, but if we are going to use them in the future as therapy, we need to form the correct type of neuron. We have evidence that during normal development, the neural precursors may in fact be turning genes on and off very rapidly over time. We hypothesise that these oscillations are important for the neural precursors to decide when they are going to respond to external signals and become a particular type of neuron. We now wish to study this further by combining mathematical models of the system with experimental manipulations in chick embryos. This will enable us to identify both the key regulatory genes that control neural development and cellular markers that will tell us how far along the neural lineage pathway a progenitor has progressed. In the long term this will allow us to control neural stem cell differentiation in a culture dish.

In order to achieve the goal of manipulating stem cells in vitro to produce particular differentiated cell types, it is essential not only to identify the extracellular signals necessary to promote specific differentiation, but also to understand the intracellular mechanisms present at different stages of the lineage pathway that restrict pluripotent progenitor cells to a definitive cell fate. We have evidence that there are dramatic dynamic fluctuations in gene expression during neural development, and we believe that these play a critical role in patterning the developing nervous system. We will integrate bioinformatics, mathematical modelling and experimental manipulations to address whether the fluctuations we observe are temporal oscillations that underlie a cell's decision to exit the cell cycle and differentiate and thus co-ordinate controlled progression of differentiation during neurogenesis. By analysing conserved regulatory elements across the genome, we will identify novel constituents of the neurogenic network. Qualitative models are insufficient to understand the dynamics of this network, and we will use mathematical models to explore the dynamical consequences of potential functional interactions between these new and already known components of the neurogenic network. By studying the behaviour of the models, we will identify key components and interactions that drive neurogenesis, together with critical network parameters such as the protein half-lives. Insight gained from the modelling studies will be complemented by directed in ovo manipulations that will initially determine quantitative values for key network parameters and subsequently test the validity of these models.