Genome Assemblies across the Diverse Evolutionary Spectrum of Leishmania Protozoan Parasites.

We report the high-quality draft assemblies and gene annotations for 13 species and/or strains of the protozoan parasite genera Leishmania, Endotrypanum, and Crithidia, which span the phylogenetic diversity of the subfamily Leishmaniinae within the kinetoplastid order of the phylum Euglenazoa. These resources will support studies on the origins of parasitism.

EuPathDB: The Eukaryotic Pathogen Genomics Database Resource.

Fighting infections and developing novel drugs and vaccines requires advanced knowledge of pathogen's biology. Readily accessible genomic, functional genomic, and population data aids biological and translational discovery. The Eukaryotic Pathogen Database Resources ( http://eupathdb.org ) are data mining resources that support hypothesis driven research by facilitating the discovery of meaningful biological relationships from large volumes of data. The resource encompasses 13 sites that support over 170 species including pathogenic protists, oomycetes, and fungi as well as evolutionarily related nonpathogenic species. EuPathDB integrates preanalyzed data with advanced search capabilities, data visualization, analysis tools and a comprehensive record system in a graphical interface that does not require prior computational skills. This chapter describes guiding concepts common across EuPathDB sites and illustrates the powerful data mining capabilities of some of the available tools and features.

Understanding Mucor circinelloides pathogenesis by comparative genomics and phenotypical studies.

The increasing number of infections by species of Mucorales and their high mortality constitute an important concern for public health. This study aims to decipher the genetic basis of Mucor circinelloides pathogenicity, which displays virulence in a strain dependent manner. Assuming that genetic differences between strains may be linked to different pathotypes, we have conducted a study to explore genes responsible for virulence in M. circinelloides by whole genome sequencing of the avirulent strain NRRL3631 and comparison with the virulent strain CBS277.49. This genome analysis revealed 773 truncated, discontiguous and absent genes in the NRRL3631 strain. We also examined phenotypic traits resulting in reduced heat stress tolerance, chitosan content and lower susceptibility to toxic compounds (calcofluor white and sodium dodecyl sulphate) in the virulent strain, suggesting the influence of cell wall on pathogenesis. Based on these results, we focused on studying extracellular protein-coding genes by gene deletion and further pathotype characterization of mutants in murine models of pulmonary and systemic infection. Deletion of gene ID112092, which codes for a hypothetical extracellular protein of unknown function, resulted in significant reduction of virulence. Although pathogenesis is a multifactorial process, these findings highlight the crucial role of surface and secreted proteins in M. circinelloides virulence and should promote further studies of other differential genes.

EuPathDB: the eukaryotic pathogen genomics database resource.

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host-pathogen interactions.

Companion: a web server for annotation and analysis of parasite genomes.

Currently available sequencing technologies enable quick and economical sequencing of many new eukaryotic parasite (apicomplexan or kinetoplastid) species or strains. Compared to SNP calling approaches, de novo assembly of these genomes enables researchers to additionally determine insertion, deletion and recombination events as well as to detect complex sequence diversity, such as that seen in variable multigene families. However, there currently are no automated eukaryotic annotation pipelines offering the required range of results to facilitate such analyses. A suitable pipeline needs to perform evidence-supported gene finding as well as functional annotation and pseudogene detection up to the generation of output ready to be submitted to a public database. Moreover, no current tool includes quick yet informative comparative analyses and a first pass visualization of both annotation and analysis results. To overcome those needs we have developed the Companion web server (http://companion.sanger.ac.uk) providing parasite genome annotation as a service using a reference-based approach. We demonstrate the use and performance of Companion by annotating two Leishmania and Plasmodium genomes as typical parasite cases and evaluate the results compared to manually annotated references.

TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei.

The metabolic network of a cell represents the catabolic and anabolic reactions that interconvert small molecules (metabolites) through the activity of enzymes, transporters and non-catalyzed chemical reactions. Our understanding of individual metabolic networks is increasing as we learn more about the enzymes that are active in particular cells under particular conditions and as technologies advance to allow detailed measurements of the cellular metabolome. Metabolic network databases are of increasing importance in allowing us to contextualise data sets emerging from transcriptomic, proteomic and metabolomic experiments. Here we present a dynamic database, TrypanoCyc (http://www.metexplore.fr/trypanocyc/), which describes the generic and condition-specific metabolic network of Trypanosoma brucei, a parasitic protozoan responsible for human and animal African trypanosomiasis. In addition to enabling navigation through the BioCyc-based TrypanoCyc interface, we have also implemented a network-based representation of the information through MetExplore, yielding a novel environment in which to visualise the metabolism of this important parasite.