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Durham e-Theses
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Unravelling the Activity of a Novel Plant Growth Modulator

BRUCE, DANIEL,JAMES (2024) Unravelling the Activity of a Novel Plant Growth Modulator. Doctoral thesis, Durham University.

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Abstract

The coordination of plant growth is achieved through a range of hormonal signalling processes that are of great academic and commercial interest. The first half of this project explores the mechanism of eW5, a novel naphthalenesulfonamide synthetic modulator of plant growth, through a series of biophysical and genetic studies.

The growth-enhancing effect of eW5 in Arabidopsis thaliana and its structural similarity with pyrabactin fed the hypothesis that eW5 interacted with proteins in the PYR1-like (PYL) family, which regulate abscisic acid signalling. Thermal shift assay, surface plasmon resonance and microscale thermophoresis experiments with ew5 and PYL proteins provided evidence of weak interactions between eW5 and PYR1, PYL1, PYL2 and PYL5. A forward genetic study was performed with EMS-mutagenised A. thaliana to identify genes responsible for a seedling hypocotyl elongation response
to eW5 that identified nine genes of interest linked to plant development.

The second half of the thesis focuses on method development for techniques useful both within the project and beyond. Hypocotyl elongation assays often involve a significant time investment to accurately measure hypocotyl lengths. A data processing pipeline was devised to automate data analysis. An R-CNN was trained to identify regions containing hypocotyls in MS-agar Petri dish images of A. thaliana seedlings. The resulting model demonstrated poor accuracy in determining the position of hypocotyls in crowded images.

Finally, contributions toward a novel algorithm for BioSAXS data analysis were made. Geometric parameters, including curvature, torsion and contacting residues were analysed for each protein structure in a survey of high-resolution crystallographic data from the Protein Data Bank to provide a distribution of probable curve geometries during model refinement. A web server for data submission and automatic preprocessing was created to simplify the process of utilising the algorithm for inexperienced users.

Item Type:Thesis (Doctoral)
Award:Doctor of Philosophy
Faculty and Department:Faculty of Science > Biological and Biomedical Sciences, School of
Thesis Date:2024
Copyright:Copyright of this thesis is held by the author
Deposited On:24 Sep 2024 13:11

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