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Public Library of Science, PLoS Neglected Tropical Diseases, 4(6), p. e1584, 2012

DOI: 10.1371/journal.pntd.0001584

Elsevier, International Journal of Infectious Diseases, (16), p. e34, 2012

DOI: 10.1016/j.ijid.2012.05.089

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Multiple Mitochondrial Introgression Events and Heteroplasmy in Trypanosoma cruzi Revealed by Maxicircle MLST and Next Generation Sequencing

Journal article published in 2012 by Louisa A. Messenger ORCID, Martin S. Llewellyn, Tapan Bhattacharyya ORCID, Oscar Franzén ORCID, Michael D. Lewis, Juan-David Ramírez, Hernan J. Carrasco, Bj Andersson, Michael A. Miles, B. Andresson
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is an important public health problem in Latin America. While molecular techniques can differentiate the major T. cruzi genetic lineages, few have sufficient resolution to describe diversity among closely related strains. The online availability of three mitochondrial genomes allowed us to design a multilocus sequence typing (mtMLST) scheme to exploit these rapidly evolving markers. We compared mtMLST with current nuclear typing tools using isolates belonging to the oldest and most widely occurring lineage TcI. T. cruzi is generally believed to reproduce clonally. However, in this study, distinct branching patterns between mitochondrial and nuclear phylogenetic trees revealed multiple incidences of genetic exchange within different geographical populations and major lineages. We also examined Illumina sequencing data from the TcI genome strain which revealed multiple different mitochondrial genomes within an individual parasite (heteroplasmy) that were, however, not sufficiently divergent to represent a major source of typing error. We strongly recommend this combined nuclear and mitochondrial genotyping methodology to reveal cryptic diversity and genetic exchange in T. cruzi. The level of resolution that this mtMLST provides should greatly assist attempts to elucidate the complex interactions between parasite genotype, clinical outcome and disease distribution.