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Going across temporal scales: how are oscillatory dynamics of protein expression decoded in the bursty expression of downstream genes in neurogenesis?


Faculty of Biology, Medicine and Health

, Prof Hilary Ashe Applications accepted all year round Self-Funded PhD Students Only

About the Project

In recent years, our understanding of gene expression dynamics has been transformed by the application of single cell molecular and imaging technologies. While previously it was thought that genes can be simply “on” or “off”, we now appreciate that the dynamics are more complex. For example, it is known that when a gene is “on”, transcription of DNA into mRNA is not a smooth process but it occurs in stochastic “bursts” of activity followed by silent periods. On the other hand, it has been discovered that protein dynamics are also not smooth and may show periodic fluctuations with short-periodicity (a few hours) which are called ultradian oscillations. Oscillations are thought to be a very versatile way for the cell to receive molecular information, because in addition to the mean level other characteristics such as the amplitude, the frequency and the phase with other oscillators can be interpreted by downstream genes. Oscillations are thought to keep the cell in a flexible, primed state, but other functions have also been proposed.

However, exactly how does the transcriptional machinery interpret oscillatory transcription factor dynamics is in fact completely unknown. How do the oscillatory protein dynamics interface with the evidence of bursty stochastic mRNA expression?

To gain insight into these questions, we propose to simultaneously monitor with live imaging the oscillatory dynamics of a transcription factor, neurogenin, and the transcriptional response of a downstream target neuroD. Both will be assayed by live imaging, in real time. We already have a neurogenin labelled protein that can be used for live imaging of the protein dynamics and during this project we will make an endogenous reporter of the neuroD transcription using the MS2 system.

Our work will be carried out in neural stem cells. The student will learn tissue culture, differentiation protocols for neural stem cells, CRISPR/Cas9 genome editing technology and confocal imaging/analysis.

Entry Requirements:
Candidates are expected to hold (or be about to obtain) a first class degree (or equivalent) in Molecular/Cellular/Developmental Biology. Candidates with experience in molecular biology lab projects are encouraged to apply.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit http://www.internationalphd.manchester.ac.uk

Funding Notes

Applications are invited from self-funded students. This project has a Band 2 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

References

Manning CS, Biga V, Boyd J, Kursawe J, Ymisson B, Spiller DG, Sanderson CM, Galla T, Rattray M, Papalopulu N. 2019
Quantitative single-cell live imaging links HES5 dynamics with cell-state and fate in murine neurogenesis.
Nat Commun. Jun 27;10(1):2835. doi: 10.1038/s41467-019-10734-8.


Vera M1, Tutucci E2, Singer RH3, 2019.Imaging Single mRNA Molecules in Mammalian Cells Using an Optimized MS2-MCP System. Methods Mol Biol. 2019;2038:3-20. doi: 10.1007/978-1-4939-9674-2_1.

Deignan, L., Pinheiro, M.T., Sutcliffe, C., Saunders, A., Wilcockson, S.G., Zeef, L.A.H., Donaldson, I.J. and Ashe, H.L. (2016). Regulation of the Dpp signaling-responsive transcriptional network in the Drosophila embryo. PLOS Genetics 12, e1006164. PMCID: PMC4933369

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