Abstract
The complexity of the metabolic networks in even the simplest organisms has raised new challenges in organizing metabolic information. To address this, specialized computer frameworks have been developed to capture, manage, and visualize metabolic knowledge. The leading databases of metabolic information are those organized under the umbrella of the BioCyc project, which consists of the reference database MetaCyc, and a number of pathway/genome databases (PGDBs) each focussed on a specific organism. A number of PGDBs have been developed for bacterial, fungal, and protozoan pathogens, greatly facilitating dissection of the metabolic potential of these organisms and the identification of new drug targets. Leishmania are protozoan parasites belonging to the family Trypanosomatidae that cause a broad spectrum of diseases in humans. In this work we use the LeishCyc database, the BioCyc database for Leishmania major, to describe how to build a BioCyc database from genomic sequences and associated annotations. By using metabolomic data generated in our group, we show how such databases can be utilized to elucidate specific changes in parasite metabolism.
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Acknowledgments
This work is supported by the grant DP0878227 from the Australian Research Council. We thank David P. de Souza for assistance in the preparation and analysis of metabolite extracts by GC-MS. We thank Peter D. Karp for valuable comments on the manuscript.
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Saunders, E.C., MacRae, J.I., Naderer, T., Ng, M., McConville, M.J., Likić, V.A. (2012). LeishCyc: A Guide to Building a Metabolic Pathway Database and Visualization of Metabolomic Data. In: Navid, A. (eds) Microbial Systems Biology. Methods in Molecular Biology, vol 881. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-827-6_17
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DOI: https://doi.org/10.1007/978-1-61779-827-6_17
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