Progress 03/01/08 to 02/28/11
Outputs
OUTPUTS: The data, reference material, and functionality of the Phytophthora Database have been improved in the following manner. More than 3,000 isolates from known and novel Phytophthora species (>100) have been characterized by sequencing up to 12 nuclear and mitochondrial loci to support the accurate identification of new isolates through comparison of sequence similarity to these reference isolates. Several species were analyzed to resolve their species boundaries. In P. cinnamomi, all isolates were identical at the ITS locus, despite the wide host and geographical range represented. However, in P. capsici there was considerable variation with the degree of sequence difference between some P. capsici isolates being even greater than that between several closely related species. Multigene phylogenetic analyses suggest that traditionally defined P. capsici is a complex consisting of several cryptic species. All Phytophthora ITS sequences in the database were aligned based on their original species annotation and performed phylogenetic analyses to find potential errors and to recognize potential species complexes. This analysis revealed that some accessions were clearly misidentified, as their sequences showed much higher identity to sequences from distantly related species than to the annotated species designation. The phylogenetic analysis suggests that several species other than P. capsici also are species complexes. The content of other reference materials was expanded. To support the utilization of molecular diagnostics tools, a very comprehensive review of currently available molecular diagnostics tools, relevant references, and the sequence alignments used to develop PCR-based diagnostics tools were created. Topics reviewed included techniques for molecular identification of isolates to a species level, identification of subpopulations within a species, and molecular diagnostic techniques for identification of pathogens at a genus and species level. The development of micro- and macro-arrays for identification of isolates to a species level was also reviewed. The user interface and schema of the database platform was redesigned to make it more user friendly and to accommodate new content and tools. A main function that was added to the database is a Geographic Information Systems tool. This tool allows database users to visualize the distribution of Phytophthora species and specific genotypes across environmental and geospatial contexts on a global map. Simple sequence repeats (SSRs) are choice marker systems for analyzing the structure and dynamics of pathogen populations and lineages. The SSR marker-based similarity search function has been developed to allow for the monitoring and visualization of population dynamics within individual Phytophthora species. As for education and outreach, we organized and offered a workshop on Phytophthora management and handling during the 2008 APS meeting. The data and service derived from this project was also presented during the 3rd International Phytophthora, Pythium, and related genera workshop in 2009. PARTICIPANTS: Seogchan Kang managed the project. Kang and David Geiser contributed to phylogenetic analysis and coordinated the identification and characterization of novel Phytophthora species. Michele Mansfield, Ekaterina Nikolaeva, and Hye-Seon Kim, postdoctoral associates, conducted species identification of Phytophthora isolates from various ecosystems by sequencing their ITS regions, in depth phylogenetic analyses to confirm the identification of putatively new species, and/or characterization of the P. capsici and P. cinnamomi species complexes. Bongsoo Park and Venky Moktali, graduate students in Kang's lab, curated and improved the Phytophthora Database. Seong H. Kim at Pennsylvania Department of Agriculture and Yilmaz Balci at University of Maryland collected a large number of Phytophthora isolates from forests, streams, and nurseries; these isolates were identified by sequencing the ITS region. Some of the isolates from these surveys appear to correspond to novel species, and their phenotypic and genotypic characters have been characterized. Kelly Ivors at North Carolina State University edited the Phytophthora protocol book and contributed the ITS sequence data from isolates collected in North Carolina. Mike Coffey at UC-Riverside prepared genomic DNA from cultures representing the known diversity of P. capsici and P. cinnamomi and also sequenced the ITS region of many historic cultures archived in the WPC. Frank Martin at USDA-ARS prepared a comprehensive review of all molecular diagnostics tools, analyzed the ITS data in the database, deposited most of the mitochondrial gene sequences to the database, contributed mitochondrial gene sequences for the multigene phylogeny of P. cinnamomi and P. capsici, and conducted mitochondrial haplotype analysis of these species. Nik Grunwald at USDA-ARS and Oregon State conducted a population genetic analysis of P. ramorum using SSR makers. The resulting SSR data are searchable through the database, and the geospatial origins of the characterized isolates can be visualized using the GIS tool in the database. Joe Russo built GIS tools to visualize the distribution of Phytophthora isolates on a global map. TARGET AUDIENCES: The Phytophthora Database has supported the identification of Phytophthora by researchers and regulators who work on Phytophthora and plant disease diagnosticians around the world. Genus-wide phylogenetic data served as a robust reference for taxonomists in testing if newly isolated strain belongs to a new species and describing new species. The database current has ~600 registered users from more than 50 counties. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Phytophthora is one of the most destructive groups of plant pathogens and constantly threatens agricultural and environmental systems. Given the global nature of Phytophthora problems, efforts to map and document the diversity and distribution of Phytophthora worldwide and to share this information are essential to manage Phytophthora. This project has contributed to enhancing plant and environmental biosecurity by establishing a global cyberinfrastructure that supports research and education on Phytophthora with the focus on the identification and monitoring of Phytophthora. Systematically cataloging previously characterized Phytophthora species/strains in an easily accessible format establishes a baseline that supports the accurate identification of newly isolated strains through comparison of their genetic similarity to the data archived in the database. The availability of genus-wide, multi-gene data, in the Phytophthora Database as a genus-wide phylogenetic framework has facilitated the recognition and description of numerous new species and the characterization of species complexes. The compilation of comprehensive data sets from traditional and molecular taxonomic studies into this database has also helped in the recognition of errors and inconsistencies in the existing data, which in turn has directed the elimination of these problems and the development and testing of new phylogenetic hypotheses. Recently discovered novel Phytophthora species of global significance, such as P. ramorum and P. kernoviae, are unlikely to be the last Phytophthora threats to agricultural and forest ecosystems, highlighting the importance of providing such means for data storage, sharing, and utilization to support monitoring the diversity, distribution and dynamics of Phytophthora worldwide. Given the global nature of Phytophthora problems, efforts to map and document the diversity and distribution of Phytophthora worldwide and to share this information are essential to significantly improve our ability to track and manage Phytophthora. This project has promoted and supported collaborations within the U.S. and with other countries in collecting and sharing data associated with Phytophthora. Two workshops supported by this project were well attended and resulted in a Phytophthora protocol book, which will be published by the APS Press. In addition, a number of special sessions were also organized, including: Gloria Abad and Kelly Ivors organized the special session "Refining Systematics (Taxonomy, Nomenclature, Phylogenetics) for Better Resolution in the Population Biology and Evolution of the Oomycetes" at the 2010 APS meeting. The Phytophthora Database currently has 514 registered users from more than 50 counties. On average, ~300 users visited the database per month. This project also served as a model for establishing similar community cyberinfrastructures supporting the identification and management of different pathogen groups.
Publications
- Abad, Z. G., K. L. Ivors, C. A. Gallup, J. A. Abad, and H. D. Shew. 2011. Morphological and molecular characterization of Phytophthora glovera sp. nov. from tobacco in Brazil. Mycologia 103: 341-350.
- Park, B., J. Park, K.-C. Cheong, J. Choi, J. Jung, Y.-H. Lee, T. J. Wald, K. O'Donnell, D. M. Geiser, and S. Kang. 2011. Cyber-infrastructure for Fusarium (CiF): Three integrated platforms supporting strain identification, phylogenetics, comparative genomics, and knowledge sharing. Nucleic Acids Research 39(1): D640-D646.
- Richter, B. S., K. Ivors, W. Shi, and D. M. Benson. 2011. Cellulase activity as a mechanism for suppression of Phytophthora root rot in mulches. Phytopathology 101: 223-230.
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Progress 03/01/09 to 02/28/10
Outputs
OUTPUTS: The Phytophthora Database has been improved in three areas. Firstly, the user interface and schema of the database platform was redesigned to make it more user friendly and to accommodate new content and tools. Secondly, its content was expanded. To support the utilization of molecular diagnostics tools, a very comprehensive review of currently available molecular diagnostics tools, relevant references, and the sequence alignments used to develop PCR-based diagnostics tools were posted to the database. Topics reviewed included techniques for molecular identification of isolates to a species level (sequence and PCR-RFLP based), identification of subpopulations within a species (e.g., RFLP, SNP, RAPD, AFLP, SSR, and mitochondrial haplotype analysis) and molecular diagnostic techniques for identification of pathogens at a genus and species level. The development of micro- and macro-arrays for identification of isolates to a species level is also reviewed. The predominant loci used for developing diagnostic markers (rDNA-ITS, elicitin, beta-tubulin, Ypt1 ras-related protein, and cox1 and 2 spacer) and their sequence alignments are provided to simplify development of new species-specific markers by users of the database. A comprehensive set of protocols for handling, studying, or managing Phytophthora have been assembled and will be published by the APS Press. Although many Phytophthora species have been extensively studied, species boundaries of many species still remain to be clearly defined. We conducted in depth phylogenetic and mitochondrial haplotype analyses of P. cinnamomi and P. capsici. In P. cinnamomi, all isolates were identical at the ITS locus, despite the wide host and geographical range represented. However, in P. capsici there was considerable variation with the degree of sequence difference between some P. capsici isolates being even greater than that between several closely related species. Multigene phylogenetic analyses suggest that traditionally defined P. capsici is a complex consisting of several cryptic species. To assess the type and degree of potential errors associated with ITS data, we aligned all Phytophthora ITS sequences in the database based on their species annotation and performed phylogenetic analysis. Sequences that did not align well with those from other strains within the same species were then subjected to BLAST searches against the Phytophthora Database. This analysis revealed that some accessions were clearly misidentified, as their sequences showed much higher identity to sequences from distantly related species than to the annotated species designation. The phylogenetic analysis suggests that several species other than P. capsici are species complexes. ITS sequences from 1,200 new isolates have also been generated and are currently being curated. Lastly, to support the monitoring and visualization of the distribution and change of Phytophthora species across environmental, geospatial and temporal contexts, Geographic Information Systems (GIS) tools were incorporated to the database; this tool allows geographic origins of selected isolates or species to be presented on a global map. PARTICIPANTS: Seogchan Kang managed the project. Kang and David Geiser contributed to phylogenetic analysis and coordinated the identification and characterization of novel Phytophthora species. Michele Mansfield and Ekaterina Nikolaeva, postdoctoral associates in Kang's lab, conducted species identification of Phytophthora isolates from various ecosystems and in depth phylogenetic analyses to confirm the identification of putatively new species and to characterize the P. capsici and P. cinnamomi species complexes. Bongsoo Park and Venky Moktali, graduate students in Kang's lab, curated and improved the Phytophthora Database. Seong H. Kim at Pennsylvania Department of Agriculture and Yilmaz Balci at University of Maryland collected a large number of Phytophthora isolates from forests, streams, and nurseries; these isolates were identified by sequencing the ITS region. Some of the isolates from these surveys appear to correspond to novel species, and both phenotypic and genotypic characterizations are underway to formally describe them. Kelly Ivors at North Carolina State University edited the Phytophthora protocol book and contributed the ITS sequence data from isolates collected in North Carolina. Mike Coffey at UC-Riverside prepared genomic DNA from cultures representing the known diversity of P. capsici and P. cinnamomi and also sequenced the ITS region of many historic cultures archived in the WPC. Frank Martin at USDA-ARS prepared a comprehensive review of all molecular diagnostics tools, analyzed the ITS data in the database, contributed mitochondrial gene sequences for the multigene phylogeny of P. cinnamomi and P. capsici, and conducted mitochondrial haplotype analysis of these species. Nik Grunwald at USDA-ARS and Oregon State conducted a high-resolution population genetic analysis of P. ramorum using isolated collected from nation-wide surveys of nurseries and streams. TARGET AUDIENCES: The Phytophthora Database has supported the identification of Phytophthora by researchers and regulators who work on Phytophthora and plant disease diagnosticians around the world. Genus-wide phylogenetic data served as a robust reference for taxonomists in testing if newly isolated strain belongs to a new species and describing new species. The database current has 429 registered users in more than 50 counties. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Systematically cataloging previously characterized Phytophthora species/strains in an easily accessible format establishes a baseline that supports accurate identification and risk assessment of new isolates through comparison of genetic/phenotypic similarity to the archived isolates. The availability of genus-wide, multi-gene data, including ITS sequences, in the Phytophthora Database as a genus-wide phylogenetic framework has facilitated the recognition and description of numerous new species and the characterization of species complexes. The compilation of comprehensive data sets from traditional and molecular taxonomic studies into this platform has also helped in the recognition of errors and inconsistencies in the existing data, which in turn has directed the elimination of these problems and the development and testing of new phylogenetic hypotheses. Recently discovered novel Phytophthora species of global significance, such as P. ramorum and P. kernoviae, are unlikely to be the last Phytophthora threats to agricultural and forest ecosystems, highlighting the importance of providing such means for data storage, sharing, and utilization to support monitoring the diversity, distribution and dynamics of Phytophthora worldwide. This project has promoted and supported more cooperation within the U.S. and with other countries in collecting and sharing data associated with Phytophthora. The Phytophthora Database currently has 429 registered users in more than 50 counties. On average, ~400 users visited the database per month. Given the global nature of Phytophthora problems, efforts to map and document the diversity and distribution of Phytophthora worldwide and to share this information are essential to significantly improve our ability to track and manage Phytophthora. This project has also served as a model for establishing similar community infrastructures supporting the identification and management of different pathogen groups.
Publications
- Kang, S., M. A. Mansfield, B. Park, D. M. Geiser, K. L. Ivors, M. D. Coffey, N. Grunwald, F. M. Martin, A. Levesque, and J. E. Blair. 2010. The promise and pitfalls of sequence-based identification of plant pathogenic fungi and oomycetes. Phytopathology. (In Press).
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Progress 03/01/08 to 02/28/09
Outputs
OUTPUTS: During 2008-2009, to increase and enhance the data content of the Phytophthora Database (PD), we have conducted the following work: (i) ITS sequence-based identification of more than 1,000 Phytophthora isolates that have been collected by Dr. Seong H. Kim at the Pennsylvania Department of Agriculture, Dr. Yilmaz Balci at University of Maryland, Dr. Heung-Tae Kim at Chongbook National University in Korea, Dr. Steve Jefferes at Clemson University, and Dr. Sabine Werres at the Institute for Plant Protection in Horticulture and Forests in Germany; (ii) Characterization of new Phytophthora species based on their morphological, cultural, and molecular characteristics; and (iii) in depth phylogenetic analyses of P. cinnamomi and P. capsici to test the hypothesis that these species are species complexes. To assist molecular diagnosis of Phytophthora, a description of all known molecular diagnostic tools and corresponding references, as well as sequence alignments used to develop these diagnostic tools, have been assembled in a format that allows viewing and curation by members of the global Phytophthora community. This set of information is available through the PD. As for education and outreach, we organized and offered a workshop titled "Fighting Phytophthora: How to Detect, Investigate, and Manage Phytophthora" during the 2008 APS meeting. The data and service derived from this project was also presented during the 3rd International Phytophthora, Pythium, and related genera workshop in Turin, Italy. Both workshops were well attended (~80 people) and resulted in a protocol book, which will be published by the APS Press in the near future. PARTICIPANTS: Seogchan Kang, David Geiser, and Scott Isard managed the project and participated in analyzing phylogenetic data. Kang and Geiser coordinated the identification and characterization of novel Phytophthora species. Michele Mansfield and Ekaterina Nikolaeva, postdoctoral associates in Kang's lab, conducted species identification of Phytophthora isolates from various ecosystems and in depth phylogenetic analyses to confirm the identification of putatively new species and to characterize the P. cpasici and P. cinnamomi species complexes. Bongsoo Park and Venky Moktali, graduate students in Kang's lab, curated the Phytophthora Database. In addition to the Penn State participants listed above, researchers at Pennsylvania Department of Agriculture, University of Marytland, North Carolina State University, UC-Riverside, and USDA-ARS have contributed to this project. TARGET AUDIENCES: The Phytophthora Database supports the identification of Phytophthora by plant pathologists who work on Phytophthora diseases and plant disease diagnosticians around the world. The database current has more than 400 registered users from 41 countries. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
This project contributes to plant biosecurity by establishing a global resource supporting the identification and monitoring of Phytophthora. Multiple mechanisms, including the interactive Phytophthora identification key, a comprehensive description of all known molecular diagnostic tools for Phytophthora, protocol books on Phytophthora identification and disease management, have been developed or ar ecurrently being developed to help members of the global Phytophthora community. The GPN has also contributed to the establishment of similar databases supporting the identification and management of different pathogen groups. Systematically cataloging of previously isolated and characterized Phytophthora species/strains serves as a baseline for accurate identification and risk assessment of new isolates by comparison of genetic/phenotypic similarity to the archived isolates. This cataloging has been accomplished through the use of the Phytophthora Database (PD; www.phytophthoradb.org). Given the global nature of Phytophthora problems, efforts to map and document the diversity and distribution of Phytophthora worldwide and to share this information are essential to significantly improve our ability to track and manage Phytophthora. This project has promoted and supported more cooperation within the U.S. and with other countries in collecting and sharing data associated with Phytophthora.
Publications
- Balci, Y., S. Balci, J.E. Blair, S. Park, S. Kang, and W. MacDonald. 2008. Phytophthora quercetorum sp. nov., a novel species isolated from eastern and north-central US oak forest soils. Mycological Research 112: 906-916.
- Blair, J.E., M.D. Coffey, S.-Y. Park, D.M. Geiser, and S. Kang. 2008. A multi-locus phylogeny for Phytophthora utilizing markers derived from complete pathogen genomes. Fungal Genetics & Biology 45:266-277.
- Park, J., B. Park, N. Veeraraghavan, J.E. Blair, D. M. Geiser, S. Isard, M.A. Mansfield, E. Nikolaeva, S.-Y. Park, J. Russo, S.H. Kim, M. Greene, K.L. Ivors, Y. Balci, M. Peiman, D.C. Erwin, M.D. Coffey, K. Jung, Y.-H. Lee, A. Rossman, D. Farr, E. Cline, N.J. Grunwald, D.G. Luster, J. Schrandt, F. Martin, O.K. Ribeiro, I. Makalowska, S. and Kang. 2008. Phytophthora Database: A forensic database supporting the identification and monitoring of Phytophthora. Plant Disease 92: 966-972.
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