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This article is part of the supplement: Highlights from the Ninth International Society for Computational Biology (ISCB) Student Council Symposium 2013

Open Access Meeting abstract

An integrated approach to understand apicomplexan metabolism from their genomes

Achchuthan Shanmugasundram12*, Faviel F Gonzalez-Galarza1, Jonathan M Wastling2, Olga Vasieva1 and Andrew R Jones1

Author Affiliations

1 Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB, UK

2 Institute of Infection and Global Health, University of Liverpool, Liverpool Science Park Innovation Centre 2, 146 Brownlow Hill, Liverpool L3 5RF, UK

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BMC Bioinformatics 2014, 15(Suppl 3):A3  doi:10.1186/1471-2105-15-S3-A3

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2105/15/S3/A3


Published:11 February 2014

© 2014 Shanmugasundram 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Background

The Apicomplexa is a large phylum of intracellular parasites that show great diversity and adaptability in the various ecological niches they occupy. They are the causative agents of human and animal infections including malaria, toxoplasmosis and theileriosis, which have a huge economic and social impact. A number of apicomplexan genomes have been sequenced and are publicly available. However, the prediction of gene models and annotation of gene functions remains challenging.

Methods

We have utilised an approach called ‘metabolic reconstruction’, in which genes are systematically assigned to functions within pathways/networks [1-4]. Functional annotation and metabolic reconstruction was carried out using a semi-automatic approach, integrating genomic information with biochemical evidence from the literature. The functions were automatically assigned using a sequence similarity-based approach and protein motif information. Experimental evidence was also accommodated in the confirmation of functions and the grouping of genes into metabolic pathways.

Results

A web database named Library of Apicomplexan Metabolic Pathways (LAMP, http://www.llamp.net webcite) [5] was developed to deposit the reconstructed metabolic pathways of Toxoplasma gondii, Neospora caninum, Cryptosporidium and Theileria species and Babesia bovis. Each metabolic pathway page contains an interactive metabolic pathway map, gene annotations hyperlinked to external resources and detailed information about the metabolic capabilities. This analysis led to the identification of missing enzymes that must be present to complete the metabolic pathway and orphan genes (incorrect enzyme annotations or enzymes that are involved in salvage of metabolites) that are isolated in pathways that are otherwise absent. The compilation and annotation of metabolic pathways and the comparative analysis of the overall metabolic capabilities of apicomplexan species enabled identification of differences in their ability to synthesise or depend on hosts for several metabolites (Table 1, Additional file 1).

Table 1. A survey of the data available for the different apicomplexan genomes in LAMP. The analysis is updated from the survey table published in the previous publication [5]

Additional file 1. A colour-coded table for comparison of the presence and absence of metabolic capabilities in different apicomplexan species. The green colour denotes the presence and red colour denotes the absence of metabolic capabilities in the species. The capabilities are grouped under pathways as grouped in the maps available in LAMP. The metabolic pathways are in bold letters and the capabilities under a pathway are in regular letters. Although Plasmodium falciparum is not available in LAMP, it is provided for comparison. PfaP. falciparum, TgoToxoplasma gondii, NcaNeospora caninum, CmuCryptosporidium muris, CpaCryptosporidium parvum, ChoCryptosporidium hominis, BbovBabesia bovis, TpaTheileria parva, TaTheileria annulata.

Format: TIF Size: 401KB Download fileOpen Data

Conclusions

The carefully annotated metabolic pathways and the comparative analysis of metabolism for eight apicomplexan species are publicly available for the research community in the LAMP database (http://www.llamp.net webcite). This has improved the functional annotation immensely and led to identification of putative drug targets. The hyperlinks for LAMP metabolic pathway annotations are available from the respective gene pages of the T. gondii primary database, ToxoDB (release 9) [6], enabling a wider reach for LAMP.

Acknowledgements

LAMP web database was already published in the database issue of Nucleic acids research (January 2013). LAMP is indirectly funded through several grants from Biotechnology and Biological Sciences Research Council. Travel expenses of AS to the ISCB Student Council Symposium was funded from the BBSRC DTG studentship awarded to the University of Liverpool.

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