Research AreaDuring development, cells transition from a progenitor state to differentiation with defined timing, or to quiescence from which they may be reactivated. Understanding how such transitions and their timing are regulated is key in understanding how tissues are built, maintained, repaired or subverted in disease. In recent years, our understanding of how cells make cell state transitions has been transformed by the application of single cell molecular technology that revealed a large degree of non-genetic heterogeneity in seemingly homogeneous populations of cells. In neural progenitors, single cell imaging with unstable reporters has revealed asynchronous pulsatile fluctuations in regulatory gene expression, which is masked by static measurements of population averages. Thus, cell fate transitions may not be driven simply by genes being turned on or off, but by a change in the dynamics of gene expression for example, from fluctuating or pulsatile expression to a more stable state. Using single cell quantitative approaches, live imaging, multiple experimental model systems and mathematical modeling we have put forward the hypothesis that a mutually antagonistic interaction of a key neural progenitor transcription factor (TF) Hes1 and a microRNA, miR-9 is sufficient to generate pulsatile gene expression at the single cell level. This basic TF/miR regulatory network is capable of transitioning from pulsatile gene expression to a stable state autonomously and in a time-controlled manner. However, the timing can be “tuned” by external influences such as a change in parameters or the initial conditions. Finally, stochastic simulation of this TF/miR regulatory network led us to suggest that noise is beneficial in increasing progenitor robustness and spreading the time to differentiation. We have experience with working with multiple model systems, including Xenopus, zebrafish, Embryonic Stem cell and Neural Stem cell culture, quantitative approaches and molecular methods. We are particularly keen in conceptual integration of information coming from different fields.
Current MembersPapalopulu, Nancy (Principal Investigator/Director)
Thuret, Raphael (Post-doc)
ContactInstitution: University of Manchester Address:
Faculty of Life Sciences
Michael Smith Building
University of Manchester
M13 9PT, United Kingdom