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      PHI-base: a new interface and further additions for the multi-species pathogen–host interactions database

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          Abstract

          The pathogen–host interactions database (PHI-base) is available at www.phi-base.org. PHI-base contains expertly curated molecular and biological information on genes proven to affect the outcome of pathogen–host interactions reported in peer reviewed research articles. In addition, literature that indicates specific gene alterations that did not affect the disease interaction phenotype are curated to provide complete datasets for comparative purposes. Viruses are not included. Here we describe a revised PHI-base Version 4 data platform with improved search, filtering and extended data display functions. A PHIB-BLAST search function is provided and a link to PHI-Canto, a tool for authors to directly curate their own published data into PHI-base. The new release of PHI-base Version 4.2 (October 2016) has an increased data content containing information from 2219 manually curated references. The data provide information on 4460 genes from 264 pathogens tested on 176 hosts in 8046 interactions. Prokaryotic and eukaryotic pathogens are represented in almost equal numbers. Host species belong ∼70% to plants and 30% to other species of medical and/or environmental importance. Additional data types included into PHI-base 4 are the direct targets of pathogen effector proteins in experimental and natural host organisms. The curation problems encountered and the future directions of the PHI-base project are briefly discussed.

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          PHI-base: a new database for pathogen host interactions

          To utilize effectively the growing number of verified genes that mediate an organism's ability to cause disease and/or to trigger host responses, we have developed PHI-base. This is a web-accessible database that currently catalogs 405 experimentally verified pathogenicity, virulence and effector genes from 54 fungal and Oomycete pathogens, of which 176 are from animal pathogens, 227 from plant pathogens and 3 from pathogens with a fungal host. PHI-base is the first on-line resource devoted to the identification and presentation of information on fungal and Oomycete pathogenicity genes and their host interactions. As such, PHI-base is a valuable resource for the discovery of candidate targets in medically and agronomically important fungal and Oomycete pathogens for intervention with synthetic chemistries and natural products. Each entry in PHI-base is curated by domain experts and supported by strong experimental evidence (gene/transcript disruption experiments) as well as literature references in which the experiments are described. Each gene in PHI-base is presented with its nucleotide and deduced amino acid sequence as well as a detailed description of the predicted protein's function during the host infection process. To facilitate data interoperability, we have annotated genes using controlled vocabularies (Gene Ontology terms, Enzyme Commission Numbers and so on), and provide links to other external data sources (e.g. NCBI taxonomy and EMBL). We welcome new data for inclusion in PHI-base, which is freely accessed at .
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            The Pathogen-Host Interactions database (PHI-base): additions and future developments

            Rapidly evolving pathogens cause a diverse array of diseases and epidemics that threaten crop yield, food security as well as human, animal and ecosystem health. To combat infection greater comparative knowledge is required on the pathogenic process in multiple species. The Pathogen-Host Interactions database (PHI-base) catalogues experimentally verified pathogenicity, virulence and effector genes from bacterial, fungal and protist pathogens. Mutant phenotypes are associated with gene information. The included pathogens infect a wide range of hosts including humans, animals, plants, insects, fish and other fungi. The current version, PHI-base 3.6, available at http://www.phi-base.org, stores information on 2875 genes, 4102 interactions, 110 host species, 160 pathogenic species (103 plant, 3 fungal and 54 animal infecting species) and 181 diseases drawn from 1243 references. Phenotypic and gene function information has been obtained by manual curation of the peer-reviewed literature. A controlled vocabulary consisting of nine high-level phenotype terms permits comparisons and data analysis across the taxonomic space. PHI-base phenotypes were mapped via their associated gene information to reference genomes available in Ensembl Genomes. Virulence genes and hotspots can be visualized directly in genome browsers. Future plans for PHI-base include development of tools facilitating community-led curation and inclusion of the corresponding host target(s).
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              Ensembl Genomes 2013: scaling up access to genome-wide data

              Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2017
                03 December 2016
                03 December 2016
                : 45
                : Database issue , Database issue
                : D604-D610
                Affiliations
                [1 ]Department of Plant Biology and Crop Science, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK
                [2 ]Cambridge Systems Biology and Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge, Cambridgeshire CB2 1GA, UK
                [3 ]The European Molecular Biology Laboratory, The European Bioinformatics Institute, Hinxton, Cambridgeshire CB10 1SD, UK
                [4 ]Molecular Connections Private Limited, Basavanagudi, Bangalore 560 004, India
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +44 1582 763 133; Fax: +44 1582 760 981; Email: Martin.Urban@ 123456rothamsted.ac.uk
                Correspondence may also be addressed to Kim E. Hammond-Kosack. Tel: +44 1582 763 133; Fax: +44 1582 760 981; Email: Kim.Hammond-Kosack@ 123456rothamsted.ac.uk
                []Deceased 21 February 2016.
                Author information
                http://orcid.org/0000-0001-7582-1565
                Article
                10.1093/nar/gkw1089
                5210566
                27915230
                abc0c32a-3147-4113-9f6f-b074d66bd1eb
                © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 October 2016
                : 24 October 2016
                : 30 September 2016
                Page count
                Pages: 7
                Categories
                Database Issue
                Custom metadata
                04 January 2017

                Genetics
                Genetics

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