Engineering robustness in collective cell migration and cell state transitions
Project ID: 2531ad1521
(You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Division of Biosciences
Lead Supervisor: Mie Wong
Project Summary:
Collective cell migration is a key tissue shaping process that underlies proper form and function of complex life. There are serious consequences when this goes wrong, including birth defects, faulty wound repair, and spreading of a primary cancer to secondary sites. During organ formation in development, most collective cell movements are accompanied by cell state transitions, akin to how malignant cancers migrate and invade during metastasis. Research on collective cell migration and cell state transitions is thus valuable to both basic and translational science because it will enable improved understanding of embryonic development, tissue engineering, and cancer progression.
The Wong lab (UCL Biosciences and IPLS) recently identified a new mechanism by which self-guided migratory cells of a developing vertebrate sensory organ system adapt more robustly to environmental fluctuations via dynamically buffering varying chemokine levels in its local environment. Built on this new adaptation mechanism, the PhD project will combine cutting-edge tissue engineering and machine learning-based image analysis to elucidate the general principals behind how processes inside cells, between cells, and at the level of the entire tissue combine to enable robust collective decision-making. You will also work with mathematicians in the lab of Philip Pearce (UCL Mathematics and IPLS) to parametrise mathematical models and simulations developed by them. This combined multidisciplinary approach will facilitate precise representation of how a cell collective robustly migrates despite fluctuations, noise and stress, to form functional organs at the right time and place.
You will be trained in cutting edge-wet lab techniques in Tissue engineering and Super-resolution microscopy, and dry lab techniques in Python and Machine learning.
If you are excited by the topic and techniques, and would like to work in an interdisciplinary environment at the interface of biology and mathematics, please contact me: mie.wong@ucl.ac.uk