Aspergillus genomes and the Aspergillus cloud.

Aspergillus Genomes is a public resource for viewing annotated genes predicted by various Aspergillus sequencing projects. It has arisen from the union of two significant resources: the Aspergillus/Aspergillosis website and the Central Aspergillus Data REpository (CADRE). The former has primarily served the medical community, providing information about Aspergillus and associated diseases to medics, patients and scientists; the latter has focused on the fungal genomic community, providing a central repository for sequences and annotation extracted from Aspergillus Genomes. By merging these databases, genomes benefit from extensive cross-linking with medical information to create a unique resource, spanning genomics and clinical aspects of the genus. Aspergillus Genomes is accessible from http://www.aspergillus-genomes.org.uk.

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 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.