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Open Access Highly Accessed Research article

The Schistosoma mansoni phylome: using evolutionary genomics to gain insight into a parasite’s biology

Larissa Lopes Silva123, Marina Marcet-Houben45, Laila Alves Nahum126, Adhemar Zerlotini27, Toni Gabaldón45 and Guilherme Oliveira12*

Author Affiliations

1 Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou. Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais. Fundação Oswaldo Cruz - FIOCRUZ, Belo Horizonte, MG, 30190-002, Brazil

2 Centro de Excelência em Bioinformática, Fundação Oswaldo Cruz – FIOCRUZ, Belo Horizonte, MG, Brazil

3 Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais – UFMG, Belo Horizonte, MG, Brazil

4 Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader, 88, 08003, Barcelona, Spain

5 Universitat Pompeu Fabra (UPF), 08003, Barcelona, Spain

6 Faculdade Infórium de Tecnologia, Belo Horizonte, MG, 30130-180, Brazil

7 Laboratório Multiusuário de Bioinformática, Embrapa Informática Agropecuária, Campinas, São Paulo, Brazil

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BMC Genomics 2012, 13:617  doi:10.1186/1471-2164-13-617

Published: 13 November 2012

Abstract

Background

Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni’s proteome evolution and to improve its functional annotation.

Results

Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org webcite).

Conclusions

In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into host-parasite interactions. Taking advantage of a proteome-wide perspective rather than focusing on individual proteins, we identified that this parasite has experienced specific gene duplication events, particularly affecting genes that are potentially related to the parasitic lifestyle. These innovations may be related to the mechanisms that protect S. mansoni against host immune responses being important adaptations for the parasite survival in a potentially hostile environment. Continuing this work, a comparative analysis involving genomic, transcriptomic, and proteomic data from other helminth parasites, other parasites, and vectors will supply more information regarding parasite’s biology as well as host-parasite interactions.

Keywords:
Phylogenomics; Maximum likelihood analysis; Homology prediction; Functional annotation; Paralogous families; Parasite genomics; Schistosomiasis