Plant Pathogen Sensing for Early Disease Control

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Abstract

Sclerotinia sclerotiorum, a fungal pathogen of over 400 plant species has been estimated to cost UK based farmers approximately £20 million per year during severe outbreak (Oerke and Dehne 2004). S. sclerotiorum disease incidence is difficult to predict as outbreaks are often sporadic. Ascospores released from the fruiting bodies or apothecia can be dispersed for tens of kilometres. This makes disease control problematic and with no S. sclerotiorum resistant varieties available, growers are forced to spray fungicides up to three times per flowering season in anticipation of the arrival of this devastating disease. This thesis reports the development of the first infield S. sclerotiorum biosensor which aims to enable rapid detection of airborne ascospores, promoting a more accurate disease risk assessment and fungicide spraying regime. The sensor is designed to detect the presence of oxalic acid, the main pathogenicity factor secreted during early S. sclerotiorum ascospore germination. Upon electrochemical detection of this analyte in the biosensor, a binary output is relayed to farmer to warm him of a disease risk. This project focused on the development of a nutrient matrix which was designed to be contained within the biosensor. The role of this matrix was to promote the growth of captured airborne S. sclerotiorum ascospores and induce high levels of oxalic acid secretion. The use of the designed biological matrix to promote oxalic acid production was tested during three field trials in S. sclerotiorum artificially inoculated fields. This thesis describes the use of contemporary pathogenomics technologies to further investigate candidate genes involved in pathogenicity alongside the secretion of oxalic acid. A pre-described bioinformatics pipeline was used to predict the S. sclerotiorum secretome to identify potential effector proteins as well as explore proteins which are unique to S. sclerotiorum to be used as other novel targets for detection. GFP tagged constructs were designed to investigate the expression of the putative targets for S. sclerotiorum detection. The transcriptomes of wild type and oxalic acid deficient S. sclerotiorum strains during infection as well as during a saprotrophic stage were investigated. This study provided expression support for not only some of the unannotated genes identified in the putative secretome, but some candidate genes speculated to be involved in infection.

Layman's Abstract

This thesis describes the development of the first automated, infield biosensor which aims to detect the devastating fungal pathogen, Sclerotinia sclerotiorum. This fungus causes disease in many agricultural crops including oilseed rape, carrots and beans. The biosensor system aims to detect the fungal spores as they are blown into fields and relay this information to the farmer to provide an improved disease risk assessment. This will assist farmers in applying more targeted fungicide sprays when there is risk of disease which will have environmental benefits as well as cost savings. An investigation into the identification of proteins which are unique to this fungus was undertaken so that the protein targets can be used in future disease diagnostic systems. During this investigation, the molecular mechanisms used by the fungus to cause disease were studied in parallel.

Keyword(s)

Bioinformatics; Biosensor; Detection Targets; Plant Pathology; Sclerotinia sclerotiorum

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