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Modelling the dynamics of neural tube development, PhD Studentship (Funded by the QUEX Institute)

Posted by , on 11 August 2022

Job type: PhD

Location: Brisbane, Australia and Exeter, UK

Closing Date: 31 August 2022

Join a world-leading, cross-continental research team

The University of Exeter and the University of Queensland are seeking exceptional students to join a world-leading, cross-continental research team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most talented doctoral students to work closely with world-class research groups and benefit from the combined expertise and facilities offered at the two institutions, with a lead supervisor within each university. This prestigious programme provides full tuition fees, stipend, travel funds and research training support grants to the successful applicants.  The studentship provides funding for up to 42 months (3.5 years).

The closing date for applications is midnight on Tuesday 30th August 2022 (BST), with interviews taking place week commencing 19th September 2022. The start date is expected to be Monday 9th January 2023.

Supervisors:

Exeter Academic Lead:

Dr David Richards, Physics and Astronomy, University of Exeter.

Queensland Academic Lead:

Dr Melanie White, GL Institute for Molecular Bioscience, University of Queensland.

Project Summary:

How the central nervous system develops from its embryonic precursor, the neural tube, is still only poorly understood. Rectifying this is important since incorrect formation of the neural tube leads to developmental defects that account for some of the most common and severe birth defects in humans. As such, this topic is crucial for healthy living, particularly for ensuring healthy lives of children and improving global life expectancy.  Progress in this area has been hampered by the lack of an animal model that is sufficiently close to human but is still genetically tractable. Avian embryos are a better model of human neural tube development than fish or rodents, but their utility has been hampered by the difficulty of making transgenic birds. However, we have recently been involved in developing an innovative, novel quail model that has the potential to lead to a step change in the field. Importantly, this model has a substantially shorter generation time than the chicken and a number of key transgenic lines have recently been developed.

To make progress, a purely experimental approach is unlikely to be optimal. Instead a multidisciplinary approach that intimately combines mathematical modelling, computer simulation, live imaging and automatic image analysis is needed. By combining a theoretical group at the University of Exeter with an experimental group at the University of Queensland, this is precisely what this PhD will involve.  This cross-disciplinary PhD will involve the student spending time in both the Richards Group in the Living Systems Institute (Exeter), performing the mathematical modelling, computer simulations and image analysis, and the Dynamics of Morphogenesis Lab (Queensland), capturing time-lapse images of neural tube formation.

The student will also join the new Quantitative Health Network in Exeter in order to obtain a broad understanding of the role of mathematical modelling throughout biology and human health.  The project will investigate the dynamic mechanisms that control neural tube development, focusing on the roles of cell fate determination, the biophysical forces involved, the role of the actin cytoskeleton, and the spatiotemporal coordination across multiple scales.  Public involvement will also play an important part in this studentship. The student will work directly with the MAGPIEs (a group of lay people involved in medical research at the University of Exeter) in order to disseminate results, guide research and ensure that future impact is achieved.

Detailed Project Description:

This project will study how the neural tube develops in a quail animal model, with applications to understanding developmental defects that account for some of the most common and severe human birth defects.  The overall aim is to develop a novel mathematical model, driven by time-lapse imaging, of the spatiotemporal dynamics of neural tube development. This model will then be used to suggest potential avenues for tackling related birth defects. Key questions that will be addressed include how biophysical forces and cell fate specification interact to generate the spatiotemporal pattern, the role of the actin cytoskeleton, and how system robustness is achieved.  One of the chief advantages of this project is its multidisciplinary nature, intimately combining wet-lab work and theoretical work. This interdisciplinary combination is increasingly being used in both biological and biomedical research, and will give the student an excellent, highly sought-after skillset that will place them in a strong position with a broad range of future career options.

The project will involve the following three objectives:  (1) High-resolution long-term time-lapse imaging (based on expertise in Queensland). The student will perform confocal imaging of the developing neural tube in transgenic quail embryos expressing various markers of the nucleus, cell membrane, actin cytoskeleton and cell fate markers. Quail embryos will be cultured on agar-albumin in glass-bottomed imaging dishes for 48 hours from the start of neural tube formation using a protocol optimised in the White group. Cellular dynamics of the developing neural tube will be visualised by capturing confocal images every 7 minutes at 40x magnification for ~16 hours.  (2) Automatic image analysis (based on expertise in Exeter). Building on existing custom-built software within both the Richards and White groups, software will be developed that automatically segments and tracks cells in the developing neural tube. This will involve a combination of blob detection, edge detection, thresholding and Hough transforms. Tracking between frames will use a custom-built Hungarian algorithm. Cell division will be identified as in the recent work by Katie McDole et al. and others.  (3) Mathematical modelling (based on expertise in Exeter). A mathematical model/computer simulation will be designed based on a vertex model that the Richards group have already developed to describe an earlier stage of development. Cells will be described by marker points that move due to vertex-vertex forces. Vertices will be connected by springs with a tension force governed by a viscoelastic extension of Hooke’s law. Other forces will operate, including a curvature force (given by the Helfrich energy), an intracellular actin force and a volume conservation force. Cell-to-cell interaction and signalling will be included at adjacent cells.

Project timeline:

Year 1 (Queensland) – time-lapse imaging; initial image analysis development; planning of public involvement event. Deliverables: new imaging data sets.

Year 2 (Exeter) – continued image analysis development; creation of the mathematical model; public involvement event. Deliverables: bespoke image analysis algorithm.

Year 3 (Exeter and Queensland) – model validation and parameter fitting; experimental testing of model predictions. Deliverables: novel mathematical model and potential avenues for tackling birth defects.

Entry requirements

Applicants should be highly motivated and have, or expect to obtain, either a first or upper-second class BA or BSc (or equivalent) in a relevant discipline.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency.

Salary: Full tuition fees, stipend of £16,062 p.a, travel funds of up to £15,000, and RTSG of £10,715 are available over the 3.5 year studentship

Start date: 9 January 2023

Closing Date: 31 August 2022

Scientific fields: Cell biology, Quantitative biology and modelling, Computational and systems biology, Cell fate control and differentiation

Model systems: Other vertebrate

Duration: Fixed term

Minimum qualifications: First or upper-second class BA or BSc (or equivalent) in a relevant discipline.

One thought on “Modelling the dynamics of neural tube development, PhD Studentship (Funded by the QUEX Institute)”

  1. My name is Donna Stewart and I am a research writer and editor working with a group of physicians on a textbook for a non-profit called Osteopathy’s Promise for the Children. We were wondering if we could use some of your images on neural tube formation for our textbook?
    Thanking you in advance,
    Donna Stewart

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