Using mathematical modelling to understand how plant cell growth is controlled

Smithers, Euan Thomas ORCID: 0000-0002-2580-6401 (2022). Using mathematical modelling to understand how plant cell growth is controlled. University of Birmingham. Ph.D.

[img]
Preview
Smithers2022PhD.pdf
Text - Accepted Version
Available under License All rights reserved.

Download (577MB) | Preview

Abstract

Understanding plant growth is essential for a future sustainable world and to ensure food security. With a growing population there will be an increasing need for higher crop yields as well as plants that can cope with the problems that climate change will bring. Plants are also fascinatingly complex, which have many intertwining mechanical and chemical processes, with many pathways yet to be fully unravelled.

To investigate cell growth control, first on the microscale, we derive and analyse a simple mathematical model for the effective mechanical properties of the evolving cell wall network, incorporating cellulose microfibres, which reorient with cell growth and are linked via biological hotspots made up of regions of crosslinking hemicellulose. Assuming a viscoelastic response for the cell wall and using a continuum approach, we calculate the total stress resultant of the cell wall for a given overall growth rate. By changing appropriate parameters effecting the breakage rate and viscous properties, we provide evidence for this biological hotspot hypothesis and develop a mechanistic understanding of how these enzymes work. Next, to investigate pavement cell development, a joint experimental and theoretical approach is taken. Using GFP transgenic and Atomic force microscopy, signs of chemical initiation were observed, with actin cytoskeleton observations contracting some previous studies. We combine a stochastic microtubule model, a reaction-diffusion model for the signalling processes, and a vertex-element mechanical growth model to form a novel hybrid model for pavement cell development incorporating effects at multiple spatial and time scales. Model simulations demonstrate that the currently hypothesised signalling network can reinforce but not initiate lobe formation. Lobe initiation could be generated through spatial variations in mechanical properties, differential growth rates between neighbouring cells or a buckling mechanism when growth is restricted. We conclude by discussing these results in the context of current biological research.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Supervisor(s):
Supervisor(s)EmailORCID
Dyson, RosemaryUNSPECIFIEDUNSPECIFIED
Smith, DavidUNSPECIFIEDUNSPECIFIED
Luo, GalaneUNSPECIFIEDUNSPECIFIED
Licence: All rights reserved
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Mathematics
Funders: Engineering and Physical Sciences Research Council
Subjects: Q Science > QA Mathematics
Q Science > QK Botany
URI: http://etheses.bham.ac.uk/id/eprint/12399

Actions

Request a Correction Request a Correction
View Item View Item

Downloads

Downloads per month over past year