Tipping the balance : sclerotinia sclerotiorum secreted oxalic acid suppresses host defenses by manipulating the host redox environment

Sclerotinia sclerotiorum is a necrotrophic ascomycete fungus with an extremely broad host range. This pathogen produces the non-specific phytotoxin and key pathogenicity factor, oxalic acid (OA). Our recent work indicated that this fungus and more specifically OA, can induce apoptotic-like programmed cell death (PCD) in plant hosts, this induction of PCD and disease requires generation of reactive oxygen species (ROS) in the host, a process triggered by fungal secreted OA. Conversely, during the initial stages of infection, OA also dampens the plant oxidative burst, an early host response generally associated with plant defense. This scenario presents a challenge regarding the mechanistic details of OA function; as OA both suppresses and induces host ROS during the compatible interaction. In the present study we generated transgenic plants expressing a redox-regulated GFP reporter. Results show that initially, Sclerotinia (via OA) generates a reducing environment in host cells that suppress host defense responses including the oxidative burst and callose deposition, akin to compatible biotrophic pathogens. Once infection is established however, this necrotroph induces the generation of plant ROS leading to PCD of host tissue, the result of which is of direct benefit to the pathogen. In contrast, a non-pathogenic OA-deficient mutant failed to alter host redox status. The mutant produced hypersensitive response-like features following host inoculation, including ROS induction, callose formation, restricted growth and cell death. These results indicate active recognition of the mutant and further point to suppression of defenses by the wild type necrotrophic fungus. Chemical reduction of host cells with dithiothreitol (DTT) or potassium oxalate (KOA) restored the ability of this mutant to cause disease. Thus, Sclerotinia uses a novel strategy involving regulation of host redox status to establish infection. These results address a long-standing issue involving the ability of OA to both inhibit and promote ROS to achieve pathogenic success.

An influenza virus inspired polymer system for the timed release of siRNA

Small interfering RNA silences specific genes by interfering with mRNA translation, and acts to modulate or inhibit specific biological pathways; a therapy that holds great promise in the cure of many diseases. However, the naked small interfering RNA is susceptible to degradation by plasma and tissue nucleases and due to its negative charge unable to cross the cell membrane. Here we report a new polymer carrier designed to mimic the influenza virus escape mechanism from the endosome, followed by a timed release of the small interfering RNA in the cytosol through a self-catalyzed polymer degradation process. Our polymer changes to a negatively charged and non-toxic polymer after the release of small interfering RNA, presenting potential for multiple repeat doses and long-term treatment of diseases.

Mathematical modelling of controlled drug release from polymer micro-spheres : incorporating the effects of swelling, diffusion and dissolution via moving boundary problems

Controlled drug delivery is a key topic in modern pharmacotherapy, where controlled drug delivery devices are required to prolong the period of release, maintain a constant release rate, or release the drug with a predetermined release profile. In the pharmaceutical industry, the development process of a controlled drug delivery device may be facilitated enormously by the mathematical modelling of drug release mechanisms, directly decreasing the number of necessary experiments. Such mathematical modelling is difficult because several mechanisms are involved during the drug release process. The main drug release mechanisms of a controlled release device are based on the device’s physiochemical properties, and include diffusion, swelling and erosion. In this thesis, four controlled drug delivery models are investigated. These four models selectively involve the solvent penetration into the polymeric device, the swelling of the polymer, the polymer erosion and the drug diffusion out of the device but all share two common key features. The first is that the solvent penetration into the polymer causes the transition of the polymer from a glassy state into a rubbery state. The interface between the two states of the polymer is modelled as a moving boundary and the speed of this interface is governed by a kinetic law. The second feature is that drug diffusion only happens in the rubbery region of the polymer, with a nonlinear diffusion coefficient which is dependent on the concentration of solvent. These models are analysed by using both formal asymptotics and numerical computation, where front-fixing methods and the method of lines with finite difference approximations are used to solve these models numerically. This numerical scheme is conservative, accurate and easily implemented to the moving boundary problems and is thoroughly explained in Section 3.2. From the small time asymptotic analysis in Sections 5.3.1, 6.3.1 and 7.2.1, these models exhibit the non-Fickian behaviour referred to as Case II diffusion, and an initial constant rate of drug release which is appealing to the pharmaceutical industry because this indicates zeroorder release. The numerical results of the models qualitatively confirms the experimental behaviour identified in the literature. The knowledge obtained from investigating these models can help to develop more complex multi-layered drug delivery devices in order to achieve sophisticated drug release profiles. A multi-layer matrix tablet, which consists of a number of polymer layers designed to provide sustainable and constant drug release or bimodal drug release, is also discussed in this research. The moving boundary problem describing the solvent penetration into the polymer also arises in melting and freezing problems which have been modelled as the classical onephase Stefan problem. The classical one-phase Stefan problem has unrealistic singularities existed in the problem at the complete melting time. Hence we investigate the effect of including the kinetic undercooling to the melting problem and this problem is called the one-phase Stefan problem with kinetic undercooling. Interestingly we discover the unrealistic singularities existed in the classical one-phase Stefan problem at the complete melting time are regularised and also find out the small time behaviour of the one-phase Stefan problem with kinetic undercooling is different to the classical one-phase Stefan problem from the small time asymptotic analysis in Section 3.3. In the case of melting very small particles, it is known that surface tension effects are important. The effect of including the surface tension to the melting problem for nanoparticles (no kinetic undercooling) has been investigated in the past, however the one-phase Stefan problem with surface tension exhibits finite-time blow-up. Therefore we investigate the effect of including both the surface tension and kinetic undercooling to the melting problem for nanoparticles and find out the the solution continues to exist until complete melting. The investigation of including kinetic undercooling and surface tension to the melting problems reveals more insight into the regularisations of unphysical singularities in the classical one-phase Stefan problem. This investigation gives a better understanding of melting a particle, and contributes to the current body of knowledge related to melting and freezing due to heat conduction.

Learning in host selection in Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

The effect of experience on pre- and post-alighting host selection in adult female Helicoverpa armigera was tested in an indoor flight cage, and in a large greenhouse. The moths had experienced either tobacco or tomato plants (both are hosts of H. armigera) for 3 days, or were given no experience. Individuals were then released and their host selection assessed. All individuals caught in the greenhouse were identified and tested for post-alighting acceptance on each host. Experience significantly influenced both pre- and post-alighting host selection in ovipositing moths. This modification in behaviour is attributed to 'learning', and presents the first detailed evidence for learning in moths. Possible behavioural mechanisms involved are discussed, and a hypothesis is presented regarding learning in post-alighting host acceptance. The existence of learning in H. armigera, a highly polyphagous agricultural pest, is discussed in the light of current theories on environmental predictability and the advantages of learning. Copyright 1998 The Association for the Study of Animal Behaviour.

Host selection in phytophagous insects: a new explanation for learning in adults

Insect learning can change the preferences an egg laying female displays towards different host plant species. Current hypotheses propose that learning may be advantageous in adult host selection behaviour through improved recognition, accuracy or selectivity in foraging. In this paper, we present a hypothesis for when learning can be advantageous without such improvements in adult host foraging. Specifically, that learning can be an advantageous strategy for egg laying females when larvae must feed on more than one plant in order to complete development, if the fitness of larvae is reduced when they switch to a different host species. Here, larvae benefit from developing on the most abundant host species, which is the most likely choice of host for an adult insect which increases its preference for a host species through learning. The hypothesis is formalised with a mathematical model and we provide evidence from studies on the behavioural ecology of a number of insect species which demonstrate that the assumptions of this hypothesis may frequently be fulfilled in nature. We discuss how multiple mechanisms may convey advantages in insect learning and that benefits to larval development, which have so far been overlooked, should be considered in explanations for the widespread occurrence of learning.

A general model for host plant selection in phytophagous insects

We develop a general theoretical framework for exploring the host plant selection behaviour of herbivorous insects. This model can be used to address a number of questions, including the evolution of specialists, generalists, preference hierarchies, and learning. We use our model to: (i) demonstrate the consequences of the extent to which the reproductive success of a foraging female is limited by the rate at which they find host plants (host limitation) or the number of eggs they carry (egg limitation); (ii) emphasize the different consequences of variation in behaviour before and after landing on (locating) a host (termed pre- and post-alighting, respectively); (iii) show that, in contrast to previous predictions, learning can be favoured in post-alighting behaviour--in particular, individuals can be selected to concentrate oviposition on an abundant low-quality host, whilst ignoring a rare higher-quality host; (iv) emphasize the importance of interactions between mechanisms in favouring specialization or learning.

Intra-specific variation for host plant use in Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae) : implications for management

The polyphagous moth Helicoverpa armigera (Hübner) is one of the world's most important agricultural pests. A number of existing approaches and future designs for management of H. armigera rely on the assumption that moths do not exhibit either genetically and/or non-genetically based variation for host plant utilization. We review recent empirical evidence demonstrating that both these forms of variation influence host plant use in this moth. The significance of this variation in H. armigera in relation to current and future pest management strategies is examined. We provide recommendations on future research needs and directions for sustainable management of H. armigera, under a framework that includes consideration of intra-specific variation for host use relevant in this and other similar pest species.

How host plant variability influences the advantages to learning : a theoretical model for oviposition behaviour in Lepidoptera

Learning can allow individuals to increase their fitness in particular environments. The advantage to learning depends on the predictability of the environment and the extent to which animals can adjust their behaviour. Earlier general models have investigated when environmental predictability might favour the evolution of learning in foraging animals. Here, we construct a theoretical model that predicts the advantages to learning using a specific biological example: oviposition in the Lepidoptera. Our model includes environmental and behavioural complexities relevant to host selection in these insects and tests whether the predictions of the general models still hold. Our results demonstrate how the advantage of learning is maximised when within-generation variability is minimised (the local environment consists mainly of a single host plant species) and between-generation variability is maximised (different host plant species are the most common in different generations). We discuss how our results: (a) can be applied to recent empirical work in different lepidopteran species and (b) predict an important role of learning in lepidopteran agricultural pests.

Host location behaviour in the desert caterpillar, Heliothis punctifera

The host location behaviour of foraging caterpillars has received little attention, despite the wealth of theoretical and empirical studies that have been directed at this behavioural trait in adult Lepidoptera. Here, we study caterpillars of the moth Heliothis punctifera Walker (Lepidoptera: Noctuidae), which inhabits the arid inland desert areas of Australia. Caterpillars of this species consume many flowerheads before completing development and can be observed moving across the sand in search of new hosts. Consequently, if host location behaviour favours attraction to certain plant species, it might be expected to influence the distribution and abundance of caterpillars in the field. We present field data showing that H. punctifera caterpillars are unevenly distributed throughout mixed patches of two of its host species, with a higher abundance on Senecio gregorii F. Muell., the annual yellow top, compared to Myriocephalus stuartii (F. Muell. & Sond.) Benth., the poached egg daisy (both Asteraceae). Using laboratory studies, we test whether this distribution may, in part, be due to host location behaviour of caterpillars. Our results show that caterpillars exhibit a preference for locating S. gregorii in their pre- and post-contact foraging behaviour. In addition, our results provide evidence that feeding history plays a role in host location behaviour in this insect. We propose that key features of the desert environment and the ecology of H. punctifera would favour adaptations to host location behaviour by immatures.

Can mechanism help explain insect host choice?

Evolutionary theory predicts that herbivorous insects should lay eggs on plants in a way that reflects the suitability of each plant species for larval development. Empirical studies, however, often fail to find any relationship between an adult insect’s choice of host–plant and offspring fitness, and in such cases, it is generally assumed that other ‘missing’ factors (e.g. predation, host–plant abundance, learning and adult feeding sites) must be contributing to overall host suitability. Here, I consider an alternative theory – that a fitness cost inherent in the olfactory mechanism could constrain the evolution of insect host selection. I begin by reviewing current knowledge of odour processing in the insect antennal lobe with the aid of a simple schematic: the aim being to explain the workings of this mechanism to scientists who do not have prior knowledge in this field. I then use the schematic to explore how an insect’s perception of host and non-host odours is governed by a set of processing rules, or algorithm. Under the assumptions of this mechanistic view, the perception of every plant odour is interrelated, and seemingly bad host choices can still arise as part of an overall adaptive behavioural strategy. I discuss how an understanding of mechanism can improve the interpretation of theoretical and empirical studies in insect behaviour and evolution.

Quantitative evaluation of polymer gel dosimeters by broadband ultrasound attenuation

Ultrasound has been examined previously as an alternative readout method for irradiated polymer gel dosimeters, with authors reporting varying dose response to ultrasound transmission measurements. In this current work we extend previous work to measure the broadband ultrasound attenuation (BUA) response of irradiated PAGAT gel dosimeters, using a novel ultrasound computed tomography system.

Reconstructing 3D x-ray CT images of polymer gel dosimeters using the zero-scan method

In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels.

Mathematical modelling of tumour growth and interaction with host tissue and the immune system

In this thesis, three mathematical models describing the growth of solid tumour incorporating the host tissue and the immune system response are developed and investigated. The initial model describes the dynamics of the growing tumour and immune response before being extended in the second model by introducing a time-varying dendritic cell-based treatment strategy. Finally, in the third model, we present a mathematical model of a growing tumour using a hybrid cellular automata. These models can provide information to pre-experimental work to assist in designing more effective and efficient laboratory experiments related to tumour growth and interactions with the immune system and immunotherapy.

Deformation and failure of graphene sheet and graphene-polymer interface

With a monolayer honeycomb-lattice of sp2-hybridized carbon atoms, graphene has demonstrated exceptional electrical, mechanical and thermal properties. One of its promising applications is to create graphene-polymer nanocomposites with tailored mechanical and physical properties. In general, the mechanical properties of graphene nanofiller as well as graphene-polymer interface govern the overall mechanical performance of graphene-polymer nanocomposites. However, the strengthening and toughening mechanisms in these novel nanocomposites have not been well understood. In this work, the deformation and failure of graphene sheet and graphene-polymer interface were investigated using molecular dynamics (MD) simulations. The effect of structural defects on the mechanical properties of graphene and graphene-polymer interface was investigated as well. The results showed that structural defects in graphene (e.g. Stone-Wales defect and multi-vacancy defect) can significantly deteriorate the fracture strength of graphene but may still make full utilization of corresponding strength of graphene and keep the interfacial strength and the overall mechanical performance of graphene-polymer nanocomposites.

Thermal transport in graphene-polymer nanocomposites

Graphene-polymer nanocomposites have attracted considerable attention due to their unique properties, such as high thermal conductivity (~3000 W mK-1), mechanical stiffness (~ 1 TPa) and electronic transport properties. Relatively, the thermal performance of graphene-polymer composites has not been well investigated. The major technical challenge is to understand the interfacial thermal transport between graphene nanofiller and polymer matrix at small material length scale. To this end, we conducted molecular dynamics simulations to investigate the thermal transport in graphene-polyethylene nanocomposite. The influence of functionalization with hydrocarbon chains on the interfacial thermal conductivity was studied, taking into account of the effects of model size and thermal conductivity of graphene. The results are considered to contribute to development of new graphene-polymer nanocomposites with tailored thermal properties.