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A Relational Database for the Discovery of Genes Encoding Amino Acid Biosynthetic Enzymes in Pathogenic Fungi

Fungal phytopathogens continue to cause major economic impact, either directly, through crop losses, or due to the costs of fungicide application. Attempts to understand these organisms are hampered by a lack of fungal genome sequence data. A need exists, however, to develop specific bioinformatics...

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Detalles Bibliográficos
Autores principales: Giles, Peter F., Soanes, Darren M., Talbot, Nicholas J.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2003
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447380/
https://www.ncbi.nlm.nih.gov/pubmed/18629094
http://dx.doi.org/10.1002/cfg.236
Descripción
Sumario:Fungal phytopathogens continue to cause major economic impact, either directly, through crop losses, or due to the costs of fungicide application. Attempts to understand these organisms are hampered by a lack of fungal genome sequence data. A need exists, however, to develop specific bioinformatics tools to collate and analyse the sequence data that currently is available. A web-accessible gene discovery database (http://cogeme.ex.ac.uk/biosynthesis.html) was developed as a demonstration tool for the analysis of metabolic and signal transduction pathways in pathogenic fungi using incomplete gene inventories. Using Bayesian probability to analyse the currently available gene information from pathogenic fungi, we provide evidence that the obligate pathogen Blumeria graminis possesses all amino acid biosynthetic pathways found in free-living fungi, such as Saccharomyces cerevisiae. Phylogenetic analysis was also used to deduce a gene history of succinate-semialdehyde dehydrogenase, an enzyme in the glutamate and lysine biosynthesis pathways. The database provides a tool and methodology to researchers to direct experimentation towards predicting pathway conservation in pathogenic microorganisms.