A biosensor is an analytical device, which incorporates a biological sensing element integrated within a physicochemical transducer. The aim of a biosensor is to produce an electronic signal, which is proportional to the interaction of analytes with the sensing element. This means that the sensor essentially transforms molecular interactions into a digital signal, thereby making detection of analytes label-free. Biosensors are used for detection of analytes ranging from small drug molecules to food- and waterborne microorganisms as well as biowarfare pathogens.
In future farming, plant production will be concentrated at few and very large farms. In order to reduce the pesticide use, it is necessary for the farm manager to have detailed knowledge of the distribution of weeds, diseases and pests within the fields. However, field-monitoring by manual inspection is time consuming and expensive. Biosensors, that can detect and quantify specific plant pathogens and map these to defined positions within the field, would enable the farm manager to perform a precise and targeted application of pesticides and thereby reduce and optimise the use of agrochemicals. The ideal scenario for precision agriculture is to have real-time, robust and low-cost sensors, for both soil and air, which can be operated by personnel with limited or no training in plant pathology.
In the present thesis focus is put on the development of immunological sensors for detection of two model plant pathogens, Puccinia striiformis f.sp. tritici, the cause of wheat yellow rust and Phytophthora infestans, the cause of late blight disease in potato.
As no antibody existed against urediniospores from P. striiformis, mouse monoclonal antibodies (mAbs) were produced and characterised. IgM-isotype mAbs from nine hybridoma cell lines were screened for cross-reactivity against representatives from common genera. Two specific mAbs were chosen for further characterisation and used to develop a competitive ELISA (using mAb4) and a subtractive inhibition ELISA (using mAb8). The subtractive inhibition ELISA was found to be more sensitive with a detection limit of 1.5 x 105 urediniospores/ml. The assay setup consists of incubation of urediniospores with mAb8, removal of urediniospore-bound mAb8 by centrifugation and quantification of the remaining unbound mAb8 by rabbit anti-mouse IgM antibody. The remaining free mAb8 is thereby related to the initial cell concentration. Assay performance was investigated by cross-reactivity studies against other rust fungi. Cross-reactivity was found with Puccinia recondita and Puccinia hordei, suggesting that the ~ 39 kDa mAb8-antigen might be a conserved structural component in the surface of Puccinia species.
The subtractive inhibition assay was further developed for label-free detection using a Surface Plasmon Resonance sensor. The polyclonal anti-mouse IgM was immobilised on a sensor surface and used for capture and quantification of mAb8. Optimal regeneration conditions were identified and 20 mM HCl effectively regenerated the surface. The assay had a similar sensitivity as the ELISA with a detection limit of 3.1 x 105 urediniospores/ml. P. striiformis was furthermore detected in a mixture with the rust species Melampsora euphorbia, which underlined the specificity of the sensor.
A Surface Plasmon Resonance sensor was further developed for detection of P. infestans sporangia. An existing Phytophthora genera mAb (phyt/G1470) was found to be highly specific when tested for cross-reactivity against spores from ascomycetes, deuteromycetes and basidiomycetes in a subtractive inhibition ELISA. The subtractive inhibition assay was incorporated in a Surface Plasmon Resonance sensor and optimal assay and regeneration conditions were identified. Calibration curves were generated and a detection limit of 2.22 x 106 sporangia/ml was achieved. The assay analysis time of 75 minutes is superior to existing immuno- and nucleotide-based assays for P. infestans detection.
In conclusion, the results presented in this thesis describe the first use of Surface Plasmon Resonance immunosensors for plant pathogen detection and represent a first step towards the implementation of plant pathogen immunosensors on-site.
|Number of pages||111|
|Publication status||Published - Mar 2007|