Publications des scientifiques de l'IRD

Arnaud-Haond S., Moalic Y., Barnabé Christian, Ayala F. J., Tibayrenc Michel. (2014). Discriminating micropathogen lineages and their reticulate evolution through graph theory-based network analysis : the case of Trypanosoma cruzi, the agent of Chagas disease. Plos One, 9 (8), p. e103213. ISSN 1932-6203.

Titre du document
Discriminating micropathogen lineages and their reticulate evolution through graph theory-based network analysis : the case of Trypanosoma cruzi, the agent of Chagas disease
Année de publication
2014
Type de document
Article référencé dans le Web of Science WOS:000341230600005
Auteurs
Arnaud-Haond S., Moalic Y., Barnabé Christian, Ayala F. J., Tibayrenc Michel
Source
Plos One, 2014, 9 (8), p. e103213 ISSN 1932-6203
Micropathogens (viruses, bacteria, fungi, parasitic protozoa) share a common trait, which is partial clonality, with wide variance in the respective influence of clonality and sexual recombination on the dynamics and evolution of taxa. The discrimination of distinct lineages and the reconstruction of their phylogenetic history are key information to infer their biomedical properties. However, the phylogenetic picture is often clouded by occasional events of recombination across divergent lineages, limiting the relevance of classical phylogenetic analysis and dichotomic trees. We have applied a network analysis based on graph theory to illustrate the relationships among genotypes of Trypanosoma cruzi, the parasitic protozoan responsible for Chagas disease, to identify major lineages and to unravel their past history of divergence and possible recombination events. At the scale of T. cruzi subspecific diversity, graph theory-based networks applied to 22 isoenzyme loci (262 distinct Multi-Locus-Enzyme-Electrophoresis -MLEE) and 19 microsatellite loci (66 Multi-Locus-Genotypes -MLG) fully confirms the high clustering of genotypes into major lineages or "near-clades'. The release of the dichotomic constraint associated with phylogenetic reconstruction usually applied to Multilocus data allows identifying putative hybrids and their parental lineages. Reticulate topology suggests a slightly different history for some of the main "near-clades', and a possibly more complex origin for the putative hybrids than hitherto proposed. Finally the sub-network of the near-clade T. cruzi I (28 MLG) shows a clustering subdivision into three differentiated lesser near-clades ("Russian doll pattern'), which confirms the hypothesis recently proposed by other investigators. The present study broadens and clarifies the hypotheses previously obtained from classical markers on the same sets of data, which demonstrates the added value of this approach. This underlines the potential of graph theory-based network analysis for describing the nature and relationships of major pathogens, thereby opening stimulating prospects to unravel the organization, dynamics and history of major micropathogen lineages.
Plan de classement
Entomologie médicale / Parasitologie / Virologie [052]
Description Géographique
AMERIQUE LATINE
Localisation
Fonds IRD [F B010062544]
Identifiant IRD
fdi:010062544
Contact