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1.
Phytopathology ; 103(12): 1204-8, 2013 Dec.
Article in English | MEDLINE | ID: mdl-23961810

ABSTRACT

The online community resource Phytophthora database (PD) was developed to support accurate and rapid identification of Phytophthora and to help characterize and catalog the diversity and evolutionary relationships within the genus. Since its release in 2008, the sequence database has grown to cover 1 to 12 loci for ≈2,600 isolates (representing 138 described and provisional species). Sequences of multiple mitochondrial loci were added to complement nuclear loci-based phylogenetic analyses and diagnostic tool development. Key characteristics of most newly described and provisional species have been summarized. Other additions to improve the PD functionality include: (i) geographic information system tools that enable users to visualize the geographic origins of chosen isolates on a global-scale map, (ii) a tool for comparing genetic similarity between isolates via microsatellite markers to support population genetic studies, (iii) a comprehensive review of molecular diagnostics tools and relevant references, (iv) sequence alignments used to develop polymerase chain reaction-based diagnostics tools to support their utilization and new diagnostic tool development, and (v) an online community forum for sharing and preserving experience and knowledge accumulated in the global Phytophthora community. Here we present how these improvements can support users and discuss the PD's future direction.


Subject(s)
Databases, Genetic , Phytophthora/genetics , Computational Biology , DNA, Mitochondrial/genetics , Databases, Genetic/trends , Genotype , Geography , Internet , Microsatellite Repeats/genetics , Phylogeny , Phytophthora/classification , Sequence Alignment , Sequence Analysis, DNA , Species Specificity
2.
J Microbiol Methods ; 92(3): 293-300, 2013 Mar.
Article in English | MEDLINE | ID: mdl-23280254

ABSTRACT

Sclerotinia sclerotiorum (Lib.) de Bary, S. minor Jagger, S. trifoliorum Eriks, and S. homoeocarpa F.T. Benn are the most relevant plant pathogenic species within the genus Sclerotinia because of their large range of economically important hosts, including tomato, peanut, alfalfa, and turfgrass, among others. Species identification based on morphological characteristics is challenging and time demanding, especially when one crop hosts multiple species. The objective of this study was to design specific primers compatible with multiplexing, for rapid, sensitive and accurate detection and discrimination among four Sclerotinia species. Specific primers were designed for the aspartyl protease gene of S. sclerotiorum, the calmodulin gene of S. trifoliorum, the elongation factor-1 alpha gene of S. homoeocarpa, and the laccase 2 gene of S. minor. The specificity and sensitivity of each primer set was tested individually and in multiplex against isolates of each species and validated using genomic DNA from infected plants. Each primer set consistently amplified DNA of its target gene only. DNA fragments of different sizes were amplified: a 264 bp PCR product for S. minor, a 218 bp product for S. homoeocarpa, a 171 bp product for S. sclerotiorum, and a 97 bp product for S. trifoliorum. These primer sets can be used individually or in multiplex for identification of Sclerotinia spp. in pure culture or from infected plants. The multiplex assay had a lower sensitivity limit than the simplex assays (0.0001 pg/µL DNA of each species). The multiplex assay developed is an accurate and rapid tool to differentiate between the most relevant plant pathogenic Sclerotinia species in a single PCR reaction.


Subject(s)
Ascomycota/classification , Ascomycota/genetics , Mycology/methods , Polymerase Chain Reaction/methods , Ascomycota/isolation & purification , DNA Primers/genetics , Plant Diseases/microbiology , Sensitivity and Specificity
3.
Phytopathology ; 100(8): 732-7, 2010 Aug.
Article in English | MEDLINE | ID: mdl-20626276

ABSTRACT

Sequences of selected marker loci have been widely used for the identification of specific pathogens and the development of sequence-based diagnostic methods. Although such approaches offer several advantages over traditional culture-based methods for pathogen diagnosis and identification, they have their own pitfalls. These include erroneous and incomplete data in reference databases, poor or oversimplified interpretation of search results, and problems associated with defining species boundaries. In this letter, we outline the potential benefits and drawbacks of using sequence data for identification and taxonomic deduction of plant-pathogenic fungi and oomycetes, using phytophthora as a primary example. We also discuss potential remedies for these pitfalls and address why coordinated community efforts are essential to make such remedies more efficient and robust.


Subject(s)
Fungi/classification , Phytophthora/classification , Plant Diseases/microbiology , DNA, Algal , DNA, Fungal , Databases, Nucleic Acid , Fungi/genetics , Phytophthora/genetics , Sequence Analysis, DNA
4.
Plant Dis ; 92(6): 966-972, 2008 Jun.
Article in English | MEDLINE | ID: mdl-30769728

ABSTRACT

Phytophthora spp. represent a serious threat to agricultural and ecological systems. Many novel Phytophthora spp. have been reported in recent years, which is indicative of our limited understanding of the ecology and diversity of Phytophthora spp. in nature. Systematic cataloging of genotypic and phenotypic information on isolates of previously described species serves as a baseline for identification, classification, and risk assessment of new Phytophthora isolates. The Phytophthora Database (PD) was established to catalog such data in a web-accessible and searchable format. To support the identification of new Phytophthora isolates via comparison of their sequences at one or more loci with the corresponding sequences derived from the isolates archived in the PD, we generated and deposited sequence data from more than 1,500 isolates representing the known diversity in the genus. Data search and analysis tools in the PD include BLAST, Phyloviewer (a program for building phylogenetic trees using sequences of selected isolates), and Virtual Gel (a program for generating expected restriction patterns for given sequences). The PD also provides a customized means of storing and sharing data via the web. The PD serves as a model that easily can be adopted to develop databases for other important pathogen groups.

5.
Phytopathology ; 97(4): 504-11, 2007 Apr.
Article in English | MEDLINE | ID: mdl-18943291

ABSTRACT

ABSTRACT Sphinganine analog mycotoxins (SAMs) are reported in maize and maize based feeds. Our objectives were to detect and quantify fumonisins B(1) and B(2) and Alternaria toxins (AAL toxins) AAL-TA and AAL-TB and determine how agronomic practices, weather conditions, and ensiling affected the occurrence and levels in maize silage. Silage was collected at harvest and after ensiling in 2001 and 2002 from 30 to 40 dairies, representing four regions in Pennsylvania. SAMs were quantified using high pressure liquid chromatography (HPLC) with fluorescence detection and high pressure liquid chromatography-mass spectrometry HPLC-MS. The average concentrations and ranges were as follows: fumonisin B(1) 2.02 mug/g (0.20 to 10.10), fumonisin B(2) 0.98 mug/g (0.20 to 20.30), AAL-TA 0.17 mug/g (0.20 to 2.01), and AAL-TB 0.05 mug/g (0.03 to 0.90). Fumonisin B(1) was the most frequently detected toxin (92%) in all samples, followed by fumonisin B(2) (55%), AAL-TA (23%), and -TB (13%). Temperature during maize development was positively correlated with fumonisin occurrence and levels and negatively with AAL-TA, while moisture events were negatively correlated with fumonisins and positively with AAL-TA. Fumonisin levels were higher in silage harvested at later developmental stages (dough through physiological maturity). Ensiling did not affect toxin concentration nor did agronomic practices (tillage system, inoculant use, or silo type) or silage characteristics (dry matter, pH, or organic acid concentration). This is the first report of AAL-TB in silage and on factors that affect SAM frequency and levels in maize silage.

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