Computational Modelling of Plant Signalling Control: a Case Study Based on Legume Autoregulation of Nodulation

Han, Liqi (2010). Computational Modelling of Plant Signalling Control: a Case Study Based on Legume Autoregulation of Nodulation PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland.

       
Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
s41094712_PhD_finalthesis.pdf Thesis (open access) Click to show the corresponding preview/stream application/pdf 3.87MB 198
s41094712_Video_S6.wmv Supplementary video Click to show the corresponding preview/stream video/x-ms-asf 1.01MB 4
Author Han, Liqi
Thesis Title Computational Modelling of Plant Signalling Control: a Case Study Based on Legume Autoregulation of Nodulation
School, Centre or Institute School of Information Technology and Electrical Engineering
Institution The University of Queensland
Publication date 2010-08
Thesis type PhD Thesis
Supervisor Jim Hanan
Peter Gresshoff
Total pages 109
Total colour pages 25
Total black and white pages 84
Subjects 08 Information and Computing Sciences
Formatted abstract Signalling mechanisms play a vital role in plant development and function, controlling processes such as germination, branching, flowering and nodulation. However, these dynamic processes are so complex that details of their operation are still largely unknown. Endogenous signals in particular, such as those based on plant hormones and peptides, are difficult to observe and remain a critical challenge for botanic research. As an addition to conventional experimental approaches,
computational modelling has emerged as a powerful tool for understanding the complexity of signalling occurring at and between different levels of organisation in plant systems. This thesis develops new methods and strategies for using computational modelling to study a typical internal shoot-root signalling system – the autoregulation of nodulation in legumes.

Nodulation is a developmental process resulting from the symbiosis of legume plants with a group of bacteria known as rhizobia. The rhizobia colonise legume roots to house themselves and provide fixed nitrogen for the host plants. Since excessive nodulation can cause overconsumption of resources and disturbs plant growth, the legumes have developed a regulatory system – autoregulation of nodulation – to maintain the balance of nodule formation. The general framework
of this signalling system has been established based on experimental findings. It has been hypothesised that the nodule formation process in the roots induces a signal moving to the leaves, which triggers a shoot-derived inhibitor moving back to the root to inhibit further nodulation. However, due to the intricacy of internal signalling and absence of flux and biochemical data, detailed mechanisms during autoregulation of nodulation remain largely unclear. The shoot-root regulatory signals also remain unidentified. To address this, this thesis focuses on the inter-organ signalling of autoregulation of nodulation and uses functional-structural plant modelling to investigate its mechanisms.

At the technical level, there were two major challenges for using functional-structural modelling to study autoregulation of nodulation: one is reconstruction of the 3D architecture of legume roots; the other is coordination of the signalling and development processes. Using soybean as the target legume plant and the L-system-based software L-studio as the modelling and simulation platform, a series of methods and techniques have been developed in this thesis to collect root development data, reconstruct root architecture, and synchronise the multi-rate signalling and developmental processes.

At the strategic level, a new modelling approach called “Computational Complementation” has been developed in this research. The key idea is to use functional-structural modelling to complement, with hypothetical signalling mechanisms, the deficiency of an empirical model of a mutant plant where the function of autoregulation of nodulation is totally lost. If the complementation leads to a regulation result the same as or similar to the wild-type phenotype, this supports the validity of the hypothesised mechanisms. The initial application of computational complementation was to investigate whether or not wild-type soybean cotyledons provide the shoot-derived inhibitor to regulate nodule progression. Two opposing hypotheses were tested with virtual experiments: (a) cotyledons function as part of the root, incapable of producing the shoot-derived inhibitor; or (b) cotyledons function as part of the shoot, involved in regulating root nodules. The virtual-experiment results suggested that hypothesis (b) were most likely to be correct, which was confirmed by a real-plant grafting experiment. This demonstrates the feasibility of computational complementation and shows its usefulness for future applications.

Suggested future research includes exploration of better techniques for model construction, application of computational complementation to help in identifying the unknown shoot-root regulatory signals and integration of lower-scale signalling models. The modelling and simulation methods as well as the computational complementation strategy developed in this thesis can be applied beyond the study of autoregulation of nodulation. They also have the potential to be used in
wider studies on plant signalling, such as those on branching regulation, flowering control and lateral initiation.
Keyword Complex systems
L-systems
Functional-structural plant modelling
Computational biology
Synchronisation

Document type: Thesis
Collections: UQ Theses (RHD) - Official
UQ Theses (RHD) - Open Access
 
Versions
Version Filter Type
Citation counts: Google Scholar Search Google Scholar
Access Statistics: 147 Abstract Views, 254 File Downloads  -  Detailed Statistics
Created: Wed, 23 Mar 2011, 06:02:32 EST by Mr Liqi Han on behalf of Library - Information Access Service