Using a systems biology approach to elucidate transcriptional networks regulating plant defence

The phytopathogen Botrytis cinerea is responsible for the devastating grey mould disease that affects hundreds of economically important crop species. B. cinerea represents a necrotrophic pathogen that must kill host tissue before if can consume the nutrients, this distinguishes it from other biotrophic pathogens that exist parasitically. Importantly, B. cinerea is capable of infecting the model plant organism Arabidopsis thaliana. Together with the availability of the sequenced B. cinerea genome and the available molecular tools that now allow fungal genome manipulation makes the pathosystem ideal for studying necrotrophic pathogen life style from a systems biology perspective. This thesis focuses on the transcriptional responses of the A. thaliana host to B. cinerea infection. A high resolution transcriptome time series experiment was conducted to compare transcriptional variation between infected and mock infected A. thaliana leaves over 48 hours. This identified 9838 unique host genes differentially expressed over the course of infection. High resolution temporal expression profiles of genes were used to build transcriptional gene regulatory networks using a Variational Bayesian State Space Modeling technique. Approximately 56% of principle network components identified by this method and tested using a reverse genetics approaches showed an effect on defence against B. cinerea. This represents a significant increase in the predictive power (of gene essentiality) when using this method compared to classical forward genetics approaches and simple reverse genetic approaches following on from expression profiling studies. Attempts were made to resolve the local networks surrounding two of these previously uncharacterised principle network components involved in defence against B. cinerea using further transcriptome expression profiling and Yeast-1-Hybrid analysis. Subsequent re-modeling and experimental studies identified a number of high probability targets and several potential regulators of these principle network components. Overall the A. thaliana-B. cinerea interaction presents a experimentally tractable pathosystem for studying necrotrophic plant defence from a systems biology perspective.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Using a systems biology approach to elucidate transcriptional networks regulating plant defence

The phytopathogen Botrytis cinerea is responsible for the devastating grey mould disease that affects hundreds of economically important crop species. B. cinerea represents a necrotrophic pathogen that must kill host tissue before if can consume the nutrients, this distinguishes it from other biotrophic pathogens that exist parasitically. Importantly, B. cinerea is capable of infecting the model plant organism Arabidopsis thaliana. Together with the availability of the sequenced B. cinerea genome and the available molecular tools that now allow fungal genome manipulation makes the pathosystem ideal for studying necrotrophic pathogen life style from a systems biology perspective. This thesis focuses on the transcriptional responses of the A. thaliana host to B. cinerea infection. A high resolution transcriptome time series experiment was conducted to compare transcriptional variation between infected and mock infected A. thaliana leaves over 48 hours. This identified 9838 unique host genes differentially expressed over the course of infection. High resolution temporal expression profiles of genes were used to build transcriptional gene regulatory networks using a Variational Bayesian State Space Modeling technique. Approximately 56% of principle network components identified by this method and tested using a reverse genetics approaches showed an effect on defence against B. cinerea. This represents a significant increase in the predictive power (of gene essentiality) when using this method compared to classical forward genetics approaches and simple reverse genetic approaches following on from expression profiling studies. Attempts were made to resolve the local networks surrounding two of these previously uncharacterised principle network components involved in defence against B. cinerea using further transcriptome expression profiling and Yeast-1-Hybrid analysis. Subsequent re-modeling and experimental studies identified a number of high probability targets and several potential regulators of these principle network components. Overall the A. thaliana-B. cinerea interaction presents a experimentally tractable pathosystem for studying necrotrophic plant defence from a systems biology perspective

Network modeling to understand plant immunity

Deciphering the networks that underpin complex biological processes using experimental data remains a significant, but promising, challenge, a task made all the harder by the added complexity of host-pathogen interactions. The aim of this article is to review the progress in understanding plant immunity made so far by applying network modeling algorithms and to show how this computational/mathematical strategy is facilitating a systems view of plant defense. We review the different types of network modeling that have been used, the data required, and the type of insight that such modeling can provide. We discuss the current challenges in modeling the regulatory networks that underlie plant defense and the future developments that may help address these challenges

An investigation into the use of human papillomavirus type 16 virus-like particles as a delivery vector system for foreign proteins: N- and C-terminal fusion of GFP to the L1 and L2 capsid proteins

Development of vaccine strategies against human papillomavirus (HPV), which causes cervical cancer, is a priority. We investigated the use of virus-like particles (VLPs) of the most prevalent type, HPV-16, as carriers of foreign proteins. Green fluorescent protein (GFP) was fused to the N or C terminus of both L1 and L2, with L2 chimeras being co-expressed with native L1. Purified chimaeric VLPs were comparable in size (*55 nm) to native HPV VLPs. Conformation-specific monoclonal antibodies (Mabs) bound to the VLPs, thereby indicating that they possibly retain their antigenicity. In addition, all of the VLPs encapsidated DNA in the range of 6–8 kb

Supply Act (No. 1), 1981, No. 50

Motivation: Identifying regulatory modules is an important task in the exploratory analysis of gene expression time series data. Clustering algorithms are often used for this purpose. However, gene regulatory events may induce complex temporal features in a gene expression profile, including time delays, inversions and transient correlations, which are not well accounted for by current clustering methods. As the cost of microarray experiments continues to fall, the temporal resolution of time course studies is increasing. This has led to a need to take account of detailed temporal features of this kind. Thus, while standard clustering methods are both widely used and much studied, their shared shortcomings with respect to such temporal features motivates the work presented here. Results: Here, we introduce a temporal clustering approach for high-dimensional gene expression data which takes account of time delays, inversions and transient correlations. We do so by exploiting a recently introduced, message-passing-based algorithm called Affinity Propagation (AP). We take account of temporal features of interest following an approximate but efficient dynamic programming approach due to Qian et al. The resulting approach is demonstrably effective in its ability to discern non-obvious temporal features, yet efficient and robust enough for routine use as an exploratory tool. We show results on validated transcription factor–target pairs in yeast and on gene expression data from a study of Arabidopsis thaliana under pathogen infection. The latter reveals a number of biologically striking findings. Availability: Matlab code for our method is available at http://www.wsbc.warwick.ac.uk/stevenkiddle/tcap.html

Dating the origins of the maize-adapted strain of maize streak virus, MSV-A

Maize streak virus (MSV), which causes maize streak disease (MSD), is one of the most serious biotic threats to African food security. Here, we use whole MSV genomes sampled over 30 years to estimate the dates of key evolutionary events in the 500 year association of MSV and maize. The substitution rates implied by our analyses agree closely with those estimated previously in controlled MSV evolution experiments, and we use them to infer the date when the maize-adapted strain, MSV-A, was generated by recombination between two grass-adapted MSV strains. Our results indicate that this recombination event occurred in the mid-1800s, similar to 20 years before the first credible reports of MSD in South Africa and centuries after the introduction of maize to the continent in the early 1500s. This suggests a causal link between MSV recombination and the emergence of MSV-A as a serious pathogen of maize

Panicum streak virus diversity is similar to that observed for maize streak virus

Panicum streak virus (PanSV; genus Mastrevirus, family Geminiviridae) is, together with maize streak virus (MSV), sugarcane streak virus (SSV), sugarcane streak Reunion virus (SSRV) and sugarcane streak Egypt virus (SSEV), one of the currently described "African streak virus" (AfSV) species [6]. As with all the other AfSV species other than MSV, very little is known about PanSV genomic sequence diversity across Africa. Only two PanSV full genome sequences have ever been reported: one from Kenya [2], and the other from South Africa [17]. Both these genomes were isolated from Panicum maximum plants, but share only approximately 90% sequence identity. The reason this is noteworthy is that throughout mainland Africa all MSV genomes ever sampled from maize have been found to share > 97% sequence identity. Although other MSV strains sharing between 78 and 90% identity with the maize-adapted strain (MSV-A) have been described, these have all been isolated from different host species, indicating that host adaptation is probably the main force driving MSV diversification. MSV and PanSV share common vector species (leafhoppers in the genus Cicadulina) and probably also share some host species. Although the host range of PanSV is currently unknown, the MSV host range is extensive and includes P. maximum [3]. One might therefore expect that similar evolutionary forces acting on both species might result in their sharing similar patterns of both geographical and host-associated diversity. Here we describe the full genome sequences of five new PanSV isolates (including two new strains) sampled from southern and western Africa, and report that PanSV and MSV do indeed have similar patterns of diversity. We find, however, that unlike with MSV, geographical separation rather than host adaptation is possibly the dominant force driving PanSV diversification