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Design of virtual epithelia: shaping a tissue with cell mechanics and genetics


School of Biology

St Andrews United Kingdom Applied Mathematics Bioinformatics Biophysics Cell Biology Data Analysis Molecular Biology Other Other Software Engineering Statistics

About the Project

Students on this project will be based in the School of Mathematics and Statistics at the University of St Andrews, and will additionally have access to training in the School of Biology, if this is desired.

Motivation:

Morphogenesis, the shaping of tissues and organs, is driven by coordinated cell behaviours, including cell migration, proliferation and controlled cell death. Quantitative data that characterises cell-cell interactions is becoming increasingly abundant. In order to interpret these data, it is necessary to design multi-scale mathematical models of cell dynamics within a tissue. Such models can be used to incorporate hypotheses on the regulation of cell behaviour into a quantitative framework, which can then be compared to experimental data. Manipulations within the model identify new experiments that further increase our understanding of morphogenetic processes.

Here, we aim to build a virtual tissue representation of morphogenesis in the adult abdominal epidermis of the fruit fly Drosophila, i.e. the outer tissue layer of the fly abdomen. In the pupa, this tissue undergoes complex morphogenetic processes that are representative of similar phenomena in higher organisms. These processes rely on the tight regulation of many different cell behaviours. Specifically, larval epithelial cells are replaced by adult histoblasts, which migrate and divide to cover the abdomen. The larval epithelial cells ‘give way’ through a combination of cell migration, apical constriction and programmed cell death. By unravelling the complexity of these coupled processes, the newly designed computational model will open up the investigation of many biologically pressing questions. These questions include the spatial coordination of cell death and the molecular processes regulating cell migration. The investigation of tissue replacement will provide fundamental insights into the mechanisms underlying wound healing and tumour progression. Due to the high genetic similarity between organisms, any insights gained will be relevant to the study of human health.

Project:

You will use the Chaste computational framework (https://github.com/Chaste/Chaste) to construct a cell-based computational model of the Drosophila abdominal epidermis. Individual cells will be represented as polygons that deform due to forces originating within each cell or its neighbours, and biochemical reaction networks that control cell behaviour will be simulated within each cell individually. The model will recapitulate the entire morphogenetic process of the Drosophila abdomen, including death of the larval epithelial cells and histoblast migration.

In order to enable model validation, you will design and apply image analysis algorithms to quantify cell movement and deformations from in vivo time-lapse microscopy movies. You will design Bayesian Inference algorithms to parametrise the model and to quantify differences between the model and experimental data. Working closely with the Bischoff lab, you will improve the performance of the model through iterative cycles of model predictions and experimental validation.

Research environment:

You will be able to work in two labs with complementing expertise. Dr Kursawe has extensive expertise in the simulation of virtual tissues, as well as quantitative image analysis https://risweb.st-andrews.ac.uk/portal/en/persons/jochen-kursawe(c18cd22b-def7-4bf0-9494-f780aa9a3663).html), while the Bischoff lab has extensive expertise in in vivo 4D microscopy of Drosophila morphogenesis (http://synergy.st-andrews.ac.uk/bischoff/). The University of St Andrews, Scotland’s first university, offers a collaborative and supportive research environment, which provides top-level training and excellent imaging facilities. A wide range of taught courses is available at the University, which will equip you with valuable transferable skills.

Application procedure

To apply for this position, please submit a formal application to the PhD program of the School of Mathematics and Statistics at the University of St Andrews:

https://www.st-andrews.ac.uk/mathematics-statistics/prospective/pgr/

When you submit your application, please be prepared to include a cover letter, your CV, academic transcripts from your previous degrees, and contact details for two references. Applications are open until 28 February 2021.

Please direct informal enquiries to the project supervisor, Jochen Kursawe ().


Funding Notes

This 3 year PhD project is part of the competition funded PhD program of the School of Mathematics and Statistics at the University of St Andrews.

This opportunity is open to UK students and provides funding to cover a stipend and UK level tuition.

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