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      LeishCyc: a biochemical pathways database for Leishmania major

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          Abstract

          Background

          Leishmania spp. are sandfly transmitted protozoan parasites that cause a spectrum of diseases in more than 12 million people worldwide. Much research is now focusing on how these parasites adapt to the distinct nutrient environments they encounter in the digestive tract of the sandfly vector and the phagolysosome compartment of mammalian macrophages. While data mining and annotation of the genomes of three Leishmania species has provided an initial inventory of predicted metabolic components and associated pathways, resources for integrating this information into metabolic networks and incorporating data from transcript, protein, and metabolite profiling studies is currently lacking. The development of a reliable, expertly curated, and widely available model of Leishmania metabolic networks is required to facilitate systems analysis, as well as discovery and prioritization of new drug targets for this important human pathogen.

          Description

          The LeishCyc database was initially built from the genome sequence of Leishmania major (v5.2), based on the annotation published by the Wellcome Trust Sanger Institute. LeishCyc was manually curated to remove errors, correct automated predictions, and add information from the literature. The ongoing curation is based on public sources, literature searches, and our own experimental and bioinformatics studies. In a number of instances we have improved on the original genome annotation, and, in some ambiguous cases, collected relevant information from the literature in order to help clarify gene or protein annotation in the future. All genes in LeishCyc are linked to the corresponding entry in GeneDB (Wellcome Trust Sanger Institute).

          Conclusion

          The LeishCyc database describes Leishmania major genes, gene products, metabolites, their relationships and biochemical organization into metabolic pathways. LeishCyc provides a systematic approach to organizing the evolving information about Leishmania biochemical networks and is a tool for analysis, interpretation, and visualization of Leishmania Omics data (transcriptomics, proteomics, metabolomics) in the context of metabolic pathways. LeishCyc is the first such database for the Trypanosomatidae family, which includes a number of other important human parasites. Flexible query/visualization capabilities are provided by the Pathway Tools software and its Web interface. The LeishCyc database is made freely available over the Internet http://www.leishcyc.org.

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          Most cited references51

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          The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases

          MetaCyc (MetaCyc.org) is a universal database of metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are curated from the primary scientific literature, and are experimentally determined small-molecule metabolic pathways. Each reaction in a MetaCyc pathway is annotated with one or more well-characterized enzymes. Because MetaCyc contains only experimentally elucidated knowledge, it provides a uniquely high-quality resource for metabolic pathways and enzymes. BioCyc (BioCyc.org) is a collection of more than 350 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the predicted metabolic network of one organism, including metabolic pathways, enzymes, metabolites and reactions predicted by the Pathway Tools software using MetaCyc as a reference database. BioCyc PGDBs also contain predicted operons and predicted pathway hole fillers—predictions of which enzymes may catalyze pathway reactions that have not been assigned to an enzyme. The BioCyc website offers many tools for computational analysis of PGDBs, including comparative analysis and analysis of omics data in a pathway context. The BioCyc PGDBs generated by SRI are offered for adoption by any interested party for the ongoing integration of metabolic and genome-related information about an organism.
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            Comparative genomics of trypanosomatid parasitic protozoa.

            A comparison of gene content and genome architecture of Trypanosoma brucei, Trypanosoma cruzi, and Leishmania major, three related pathogens with different life cycles and disease pathology, revealed a conserved core proteome of about 6200 genes in large syntenic polycistronic gene clusters. Many species-specific genes, especially large surface antigen families, occur at nonsyntenic chromosome-internal and subtelomeric regions. Retroelements, structural RNAs, and gene family expansion are often associated with syntenic discontinuities that-along with gene divergence, acquisition and loss, and rearrangement within the syntenic regions-have shaped the genomes of each parasite. Contrary to recent reports, our analyses reveal no evidence that these species are descended from an ancestor that contained a photosynthetic endosymbiont.
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              Expansion of the BioCyc collection of pathway/genome databases to 160 genomes

              The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.
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                Author and article information

                Journal
                BMC Syst Biol
                BMC Systems Biology
                BioMed Central
                1752-0509
                2009
                5 June 2009
                : 3
                : 57
                Affiliations
                [1 ]Department of Biochemistry and Molecular Biology, University of Melbourne, Parkville, VIC 3010, Australia
                [2 ]Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, VIC 3010, Australia
                Article
                1752-0509-3-57
                10.1186/1752-0509-3-57
                2700086
                19497128
                f4431f10-9e18-4768-a5c9-7a4f1cb1fdd6
                Copyright © 2009 Doyle et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 January 2009
                : 5 June 2009
                Categories
                Database

                Quantitative & Systems biology
                Quantitative & Systems biology

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