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EASTBIO Stochastic models of gene expression in growing and dividing cells


School of Biological Sciences

Dr R Grima , Dr M El Karoui Wednesday, January 06, 2021 Competition Funded PhD Project (Students Worldwide)

About the Project

The random nature of gene expression is well established experimentally [1]. Over the past two decades, data has typically been obtained using microscopy methods where the cells are fixed. This provides a snapshot of gene expression at the time of fixation but it does not provide information about the dynamics of gene expression in the same cell. Due to advances in technology, in recent years it has become possible to obtain readouts of the mRNA and protein numbers in living cells that are growing and dividing. This has led to a large amount of data being collected over tens of generations in a cell lineage. However mathematical models to understand and analyze this live-cell data are largely missing because standard models assume non-growing cells and do not take into account cell division [2]. We have recently developed a series of models [3] that predict analytical distributions for the protein and mRNA molecule numbers and their power spectra inside growing and dividing cells. In this PhD project, the aim is to further extend these models to predict the single cell distribution of molecular concentrations; the aim is to use these models to shed light on the experimental observation of concentration homeostasis whereby the average concentration inside a cell remains roughly constant independent of the cell volume [4].

The School of Biological Sciences is committed to Equality & Diversity: https://www.ed.ac.uk/biology/equality-and-diversity

How to Apply:
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Funding Notes

This 4 year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership View Website. This opportunity is open to UK and International students and provides funding to cover stipend and UK level tuition fees. The fee difference will be covered by the University of Edinburgh for successful international applicants. Please refer to UKRI website (View Website) and Annex B of the UKRI Training Grant Terms and Conditions (View Website) for full eligibility criteria.

References

[1] Elowitz, Michael B., et al. Science 297.5584 (2002): 1183-1186

[2] Shahrezaei & Swain. PNAS 105.45 (2008): 17256-17261

[3] Beentjes et al. Physical Review E 101.3 (2020): 032403; Perez-Carrasco et al. Journal of the Royal Society Interface 17.168 (2020): 20200360; Cao & Grima. Proceedings of the National Academy of Sciences 117.9 (2020): 4682-4692; Jia & Grima. bioRxiv (2020).

[4] Padovan-Merhar, Olivia, et al. Molecular cell 58.2 (2015): 339-352.
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