Quarantine and surveillance strategies for plant pathogen detection and control

Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

The role of MicroRNAs in stress response in the resurrection plant Tripogon loliiformis

Research in this thesis focussed on the improvement of agricultural crops in increasing water use efficiency that impacts global crop productivity. The study identified key genetic regulatory mechanisms that the resurrection plant Tripogon loliiformis utilises to tolerate desiccation. Due to the conserved nature of the pathways involved, this information can be transferred for the enhancement of drought tolerance and water use efficiency in agricultural crops. Specifically this study used high throughput sequencing, microscopy and plant transformation to further the understanding of post-transcriptional regulatory mechanisms. It was shown that T. loliiformis uses microRNAs to regulate pro-survival autophagy pathways to tolerate desiccation.

Trehalose accumulation triggers autophagy during plant desiccation

Global climate change, increasingly erratic weather and a burgeoning global population are significant threats to the sustainability of future crop production. There is an urgent need for the development of robust measures that enable crops to withstand the uncertainty of climate change whilst still producing maximum yields. Resurrection plants possess the unique ability to withstand desiccation for prolonged periods, can be restored upon watering and represent great potential for the development of stress tolerant crops. Here, we describe the remarkable stress characteristics of Tripogon loliiformis, an uncharacterised resurrection grass and close relative of the economically important cereals, rice, sorghum, and maize. We show that T. loliiformis survives extreme environmental stress by implementing autophagy to prevent Programmed Cell Death. Notably, we identified a novel role for trehalose in the regulation of autophagy in T.loliiformis. Transcriptome, Gas Chromatography Mass Spectrometry, immunoblotting and confocal microscopy analyses directly linked the accumulation of trehalose with the onset of autophagy in dehydrating and desiccated T. loliiformis shoots. These results were supported in vitro with the observation of autophagosomes in trehalose treated T. loliiformis leaves; autophagosomes were not detected in untreated samples. Presumably, once induced, autophagy promotes desiccation tolerance in T.loliiformis , by removal of cellular toxins to suppress programmed cell death and the recycling of nutrients to delay the onset of senescence. These findings illustrate how resurrection plants manipulate sugar metabolism to promote desiccation tolerance and may provide candidate genes that are potentially useful for the development of stress tolerant crops.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.

The complete mitochondrial genome of the tarnished plant bug, Lygus lineolaris (Heteroptera: Miridae)

The complete mitochondrial genome of the tarnished plant bug, Lygus lineolaris, comprised 17,027 bp. The genome contained 13 protein coding regions, 22 tRNA genes and 2 ribosomal RNA genes. The gene arrangement corresponded to the common order found among insect mtDNAs which was considered to be the ancestral arrangement. The protein coding genes started with ATN and stopped with TAA or TAG. The nucleotide distribution was 76.0% A + T. The control region contained two repeat regions, one was 24 bp and the other was 161 bp. The Genbank accession for the complete L. lineolaris mt genome is EU401991.

A generic individual-based spatially explicit model as a novel tool for investigating insect-plant interactions: A case study of the behavioural ecology of frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

Unusual RNA plant virus integration in the soybean genome leads to the production of small RNAs

Horizontal gene transfer (HGT) is known to be a major force in genome evolution. The acquisition of genes from viruses by eukaryotic genomes is a well-studied example of HGT, including rare cases of non-retroviral RNA virus integration. The present study describes the integration of cucumber mosaic virus RNA-1 into soybean genome. After an initial metatranscriptomic analysis of small RNAs derived from soybean, the de novo assembly resulted a 3029-nt contig homologous to RNA-1. The integration of this sequence in the soybean genome was confirmed by DNA deep sequencing. The locus where the integration occurred harbors the full RNA-1 sequence followed by the partial sequence of an endogenous mRNA and another sequence of RNA-1 as an inverted repeat and allowing the formation of a hairpin structure. This region recombined into a retrotransposon located inside an exon of a soybean gene. The nucleotide similarity of the integrated sequence compared to other Cucumber mosaic virus sequences indicates that the integration event occurred recently. We described a rare event of non-retroviral RNA virus integration in soybean that leads to the production of a double-stranded RNA in a similar fashion to virus resistance RNAi plants.

Missing pieces in the puzzle of plant microRNAs

Plant microRNAs (miRNAs) are important regulatory switches. Recent advances have revealed many regulatory layers between the two essential processes, miRNA biogenesis and function. However, how these multilayered regulatory processes ultimately control miRNA gene regulation and connects miRNAs and plant responses with the surrounding environment is still largely unknown. In this opinion article, we propose that the miRNA pathway is highly dynamic and plastic. The apparent flexibility of the miRNA pathway in plants appears to be controlled by a number recently identified proteins and poorly characterized signaling cascades. We further propose that altered miRNA accumulation can be a direct consequence of the rewiring of interactions between proteins that function in the miRNA pathway, an avenue that remains largely unexplored.