Mathematical models of RNA interference in plants

Neofytou, Giannis (2017) Mathematical models of RNA interference in plants. Doctoral thesis (PhD), University of Sussex.

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RNA interference (RNAi), or Post-Transcriptional Gene Silencing (PTGS), is
a biological process which uses small RNAs to regulate gene expression on a
cellular level, typically by causing the destruction of specfic mRNA molecules.
This biological pathway is found in both plants and animals, and can be used
as an effective strategy in defending cells against parasitic nucleotide sequences,
viruses and transposons. In the case of plants, it also constitutes a major
component of the adaptive immune system. RNAi is characterised by the ability
to induce sequence-specific degradation of target messenger RNA (mRNAs) and
methylation of target gene sequences. The small interfering RNA produced
within the initiated cell is not only used locally but can also be transported
into neighbouring cells, thus acting as a mobile warning signal.
In the first part of the thesis I develop and analyse a new mathematical model
of the plant immune response to a viral infection, with particular emphasis
on the role of RNA interference. The model explicitly includes two different
time delays, one to represent the maturation period of undifferentiated cells,
and another to account for the time required for the RNAi propagating signal
to reach other parts of the plant, resulting in either recovery or warning of
susceptible cells. Analytical and numerical bifurcation theory is used to identify
parameter regions associated with recovery and resistant plant phenotypes, as
well as possible chronic infections. The analysis shows that the maturation time
plays an important role in determining the dynamics, and that long-term host
recovery does not depend on the speed of the warning signal but rather on the
strength of local recovery. At best, the warning signal can amplify and hasten
recovery, but by itself it is not competent at eradicating the infection.
In the second part of the thesis I derive and analyse a new mathematical
model of plant viral co-infection with particular account for RNA-mediated
cross-protection in a single plant host. The model exhibits four non-trivial
steady states, i.e. a disease-free steady state, two one-virus endemic equilibria,
and a co-infected steady state. I obtained the basic reproduction number
for each of the two viral strains and performed extensive numerical bifurcation
analysis to investigate the stability of all steady states and identified parameter
regions where the system exhibits synergistic or antagonistic interactions
between viral strains, as well as different types of host recovery. The results
indicate that the propagating component of RNA interference plays a significant role
in determining whether both viruses can persist simultaneously, and
as such, it controls whether the plant is able to support some constant level of
both infections. If the two viruses are sufficiently immunologically related, the
least harmful of the two viruses becomes dominant, and the plant experiences
In the third part of the thesis I investigate the properties of intracellular
dynamics of RNA interference and its capacity as a gene regulator by extending
a well known model of RNA interference with time delays. For each of the two
amplification pathways of the model, I consider the cumulative effects of delay
in dsRNA-primed synthesis associated with the non-instantaneous nature of
chemical signals and component transportation delay. An extensive bifurcation
analysis is performed to demonstrate the significance of different parameters,
and to investigate how time delays can affect the bi-stable regime in the model.

Item Type: Thesis (Doctoral)
Schools and Departments: School of Mathematical and Physical Sciences > Mathematics
Subjects: Q Science > QH Natural history > QH0301 Biology > QH0426 Genetics > QH0438.4 Special aspects of the subject as a whole, A-Z > QH0438.4.M33 Mathematics
Depositing User: Library Cataloguing
Date Deposited: 29 Mar 2017 08:49
Last Modified: 29 Mar 2017 08:52

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