The emergence of biological phenotypes from dynamic gene networks

This project is one of a number which are funded within the Carlota Palmer PhD programme. This four-year programme, run under the auspices of the Centre for Biomedical Modelling and Analysis, will commence in September 2016. The studentships will provide funding for a stipend (currently £16,165 per annum), research costs and UK/EU tuition fees for four years. Further details can be found here: http://www.exeter.ac.uk/bma/phd/

Location: Streatham Campus, University of Exeter, EX4 4QJ

Academic Supervisors: Professor John Terry, Mathematics, University of Exeter, Professor Ken Haynes, Biosciences, University of Exeter, Dr Jamie Walker, Mathematics, University of Exeter

Project Description

Despite considerable research effort, the mechanisms underpinning the emergence of biological phenotypes from complex gene regulatory networks (GRNs) remain largely unknown. The traditional reductionist approach in which individual genes are altered and subsequent alterations in phenotype defined overlooks two critical factors regarding gene regulation. First, gene expression and/or protein turnover (i.e. its dynamics) does not occur in isolation, but rather as part of a wider GRN. Second, perturbations to these networks, both internal (e.g. the binding affinity of a transcription factor to a promoter) and external (e.g. environmental factors such as oxidative stress), can have major effects on both the dynamics of an individual gene and the connectivity (i.e. structure) of GRN(s) within which the gene exists. Understanding these contingencies is important to gain a fundamental knowledge of how phenotypes emerge from genotypes.

In this project we will explore these questions using a combination of mathematical modelling and experimental synthetic biology. We will develop mathematical models of key network motifs that incorporate both the dynamics of individual genes and the connectivity structures within their related gene networks. Specifically these models will be systems of (stochastic) ordinary differential equations describing the evolution of gene expression and the interactions between different genes and proteins within the network. Using mathematical techniques, such as bifurcation theory and numerical continuation, we will characterise the emergent behaviour of these networks and explore the robustness of the dynamic phenotype to perturbations, both within the network and external to the network. This modelling approach will lead to a number of predictions that we may test experimentally. To do this, we will initially build four-node network motifs defined by the modelling in the yeast Saccharomyces cerevisiae using a circuit of artificial transcription factors, cognate promoters of various strengths and degron sequences that control protein turnover. This will allow us to define all edges, in all directions, within the four-node network and vary the dynamics of each node. This will be implemented using standard synthetic biology approaches. We will then test that these motifs behave with the predicted dynamics. Once the emergent phenotypes of these simple networks have been explored we will use similar methods to build more complex networks, reflecting, for example, the adrenal steroidogenic pathway, in S. cerevisiae and explore their susceptibility to changes in structure and dynamics.

Entry requirements:

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. Applicants with a Lower Second Class degree will be considered if they also have Master’s degree or have significant relevant non-academic experience. If English is not your first language you will need to have achieved at least 6.5 in IELTS (and no less than 6.0 in any section) by the start of the project (alternative tests may be acceptable, see http://www.exeter.ac.uk/postgraduate/apply/english/).