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Integrated Technologies for the Rapid Diagnosis of Known and Emerging Plant Pathogens


<OL> <LI> To develop a Multi-Pathogen Identification (MPID) microarray for the rapid detection of known and emerging pathogens of solanaceous crops <LI> To establish a disease diagnostic database of fingerprints for solanaceous plant associated bacteria using Terminal Restriction Fragment Length Polymorphism (T-RFLP) and PCR Single-Stranded Conformation Polymorphism (PCR-SSCP) <LI> To develop methods for the rapid strain differentiation of three pathogens of importance to plant biosecurity and international trade, Ralstonia solanacearum, Potato Virus Y, and Phytophthora infestans<LI> To provide information, tools, protocols and diagnostic resources for distribution to diagnostic clinics, agricultural educators, and extension personnel.

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NON-TECHNICAL SUMMARY: Diagnosing plant diseases are problematic when the pathogen cannot be observed easily or directly. The purpose of this project is to develop multi-pathogen identification technologies for known and emerging plant pathogens. The technologies to be employed are largely nucleic acid-based and will focus on solanaceous crop species. <P>

APPROACH: The project focuses three sets of technologies that are interrelated. Most of the experimental techniques rely on PCR as a means of amplifying the genetic material of pathogens. Therefore, at the core of efforts will be the identification of target sequences and primers to amplify DNAs (or cDNAs) specific to individual pathogens or groups of pathogens. Assaying for and identifying multiple pathogens simultaneously can be achieved by multiplex PCR. Multiplex (or simplex) PCR will also function to amplify sequences that can be assayed for using either of two very powerful techniques, the sampling of DNA microarrays for the detection of multiple pathogens, and microbial community analyses using DNA polymorphism techniques. The DNA microarrays will also be used to identify and in some cases genetically fingerprint species, strains or biotypes of specific pathogens. We will communicate the development of these techniques to regional diagnostic clinics. This will augment the use of well-established diagnostic techniques through outreach to and training of agricultural educators and extension personnel.
PROGRESS: 2004/06 TO 2009/05<BR>

OUTPUTS: Considerable progress has been made in developing integrated technologies for the diagnosis of plant pathogens. For the first objective on array development, the focus has been on a validation of the use of diagnostic oligonucleotides immobilized onto membranes in a macroarray format. Detailed methodologies have been described for amplifying and labeling infected-plant RNA extracts and their use in array detection of 11 viruses and a viroid (Agindotan & Perry, 2008). The virus detection macroarray has now been expanded to include probes for detecting 125 viruses and 8 viroids of solanaceous plants. An array has been completed for the detection of 43 fungal and oomycete pathogens of solanaceous crops, including 12 members of the Fusarium solani species complex and a majority of the respective pathogens of tomato (Zhang et al., 2008). The entire method, from receiving field sample to results in hand, takes 12 hours; we have used the array on field samples, and can easily detect multiple pathogens from the same sample. The viral and fungal/oomycete arrays have been combined into a multipathogen detection array with approximately 1000 probes. Phytophthora infestans and viruses have been detected simultaneously from one host plant in a single array. We utilized similar technology on a collaborative project to differentiate races of the cotton pathogen Fusarium oxysporum f. sp. vasinfectum (Gilbert et al. 2008). The second objective is to develop a database of fingerprints for plant-associated bacteria. Primer sets were designed to amplify conserved virulence genes found in bacterial plant pathogens and genes from four genera of bacterial plant pathogens have been amplified and analyzed by SSCP. Distinctive fingerprints have been observed for five species. SSCP has been used to demonstrate that many subtypes of Erwinia are involved in disease outbreaks in Wisconsin, while only one Xanthomonas campestris pathovar fingerprint has been observed from disease outbreaks in NY. The third objective was on pathogen strain differentiation. The priority in oligonucleotide design for pathogen detection has been to avoid false negatives, i.e. to ensure all strains are detected. The extension/outreach program (the fourth objective) focused on establishing contacts with and making presentations throughout the Northeast and Wisconsin in which the pathogen detection system was discussed. This has included extension talks in NY to conventional and organic growers and to extension educators, and more focused meetings with potato growers in Wisconsin. Additional outreach occurred with invited talks at national meetings and international meetings. The extension/outreach and related work is represented in abstracts from presentations at national meetings. <P>
IMPACT: 2004/06 TO 2009/05 <BR>
An important part of our national plant biosecurity is to be able to rapidly diagnose known and emerging plant pathogens. Multi-pathogen detection systems are being developed to facilitate rapid diagnoses. The availability of these systems will complement and expand upon the resources of existing diagnostic networks. The array technology was used for diagnostics in disease outbreaks of pepper (New York, Wisconsin), and multiple disease outbreaks in potato (Wisconsin, Minnesota). The methods development work is significant because pathogen detection was accomplished without the use of pathogen-specific primers for the amplification step (Agindotan & Perry, 2008). This approach contrasts with a parallel study to develop a multiplex membrane assay for potato viruses using pathogen-specific primers and described in 2006. The fungus/oomycete pathogen array (Zhang, et al., 2008) is significant because the designed probes have been shown to be efficacious and can now be incorporated into a multipathogen array. The methods have now been employed for pathogen detection in an unrelated crop, cotton (Gilbert, et al., 2008), and have been adapted for the detection of nematodes (Pokharel, et al., 2007).

Perry, Keith
Cornell University
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