Modelling the chemomechnical processes of cell competition

Lead Research Organisation: University of Oxford
Department Name: Interdisciplinary Bioscience DTP

Abstract

Competition in nature is traditionally conceptualised as a battle between individual organisms in the constant struggle for survival. The triumph of one organism results in the demise of the other. Cooperation on the other hand involves individuals acting in a mutually beneficially manner and is therefore often regarded as the opposite of competition. From the perspective of individual cells, multicellular life is perhaps the most extreme form of cooperation. However, even within multicellular organisms, cells compete for resources and space. Genetically damaged \loser" cells that grow at a slower rate than their neighbouring 'winner' cells are eliminated from the body by apoptosis. Cell competition is context-dependent; loser cells are perfectly viable if the whole organism is composed of them. The demise of loser cells is triggered specifically by the presence of cells that are perceived to be more t. Multiple triggers and pathways involved with cell competition have been discovered. For instance, differential expression of the growth regulator Myc is known to trigger cell competition through the Toll signalling pathway. However, the mechanism by which cells measure and communicate
their relative fitness remains elusive. Recent research demonstrates that some forms of cell competition are mediated by mechanical stresses. It is not clear, however, to what extent mechanical stresses contribute to classical cell competition. In this project, we will use cell-based computational models to investigate the biochemical and mechanical processes of cell competition and how they interact with one another.

BBSRC priority areas: data driven biology, systems approaches to the biosciences.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M011224/1 01/10/2015 30/09/2023
1945643 Studentship BB/M011224/1 01/10/2017 30/09/2021 Thomas Pak
 
Title Pakman: a modular, efficient and portable tool for running parallel approximate Bayesian computation algorithms. 
Description Pakman is a software tool for parallel approximate Bayesian computation (ABC) algorithms. Its modular framework is based on user executables, which means that problem-specific tasks, like model simulations, are performed by black box executables supplied to Pakman by the user. Pakman parallelises the execution of simulations using MPI, a portable standard for distributed computing, and was designed to be lightweight so that a minimal amount of overhead goes into parallelisation. The problems that will benefit the most from Pakman are those where model simulations take a relatively long time, on the order of seconds or more. 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
Impact This software was only just published, so it has not yet had the chance to be widely used. 
URL https://joss.theoj.org/papers/10.21105/joss.01716