Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

Analyses of 32 Loci Clarify Phylogenetic Relationships among Trypanosoma cruzi Lineages and Support a Single Hybridization prior to Human Contact

, *

PLoS Neglected Tropical Diseases

Public Library of Science

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      BackgroundThe genetic diversity of Trypanosoma cruzi, the etiological agent of Chagas disease, has been traditionally divided in two major groups, T. cruzi I and II, corresponding to discrete typing units TcI and TcII-VI under a recently proposed nomenclature. The two major groups of T. cruzi seem to differ in important biological characteristics, and are thus thought to represent a natural division relevant for epidemiological studies and development of prophylaxis. To understand the potential connection between the different manifestations of Chagas disease and variability of T. cruzi strains, it is essential to have a correct reconstruction of the evolutionary history of T. cruzi.Methodology/Principal FindingsNucleotide sequences from 32 unlinked loci (>26 Kilobases of aligned sequence) were used to reconstruct the evolutionary history of strains representing the known genetic variability of T. cruzi. Thorough phylogenetic analyses show that the original classification of T. cruzi in two major lineages does not reflect its evolutionary history and that there is only strong evidence for one major and recent hybridization event in the history of this species. Furthermore, estimates of divergence times using Bayesian methods show that current extant lineages of T. cruzi diverged very recently, within the last 3 million years, and that the major hybridization event leading to hybrid lineages TcV and TcVI occurred less than 1 million years ago, well before the contact of T. cruzi with humans in South America.Conclusions/SignificanceThe described phylogenetic relationships among the six major genetic subdivisions of T. cruzi should serve as guidelines for targeted epidemiological and prophylaxis studies. We suggest that it is important to reconsider conclusions from previous studies that have attempted to uncover important biological differences between the two originally defined major lineages of T. cruzi especially if those conclusions were obtained from single or few strains.

      Author Summary

      Trypanosoma cruzi is the protozoan parasite that causes Chagas disease, a major health problem in Latin America. The genetic diversity of this parasite has been traditionally divided in two major groups: T. cruzi I and II, which can be further divided in six major genetic subdivisions (subgroups TcI-TcVI). T. cruzi I and II seem to differ in important biological characteristics, and are thought to represent a natural division relevant for epidemiological studies and development of prophylaxis. Having a correct reconstruction of the evolutionary history of T. cruzi is essential for understanding the potential connection between the genetic and phenotypic variability of T. cruzi with the different manifestations of Chagas disease. Here we present results from a comprehensive phylogenetic analysis of T. cruzi using more than 26 Kb of aligned sequence data. We show strong evidence that T. cruzi II (TcII-VI) is not a natural evolutionary group but a paraphyletic lineage and that all major lineages of T. cruzi evolved recently (<3 million years ago [mya]). Furthermore, the sequence data is consistent with one major hybridization event having occurred in this species recently (< 1 mya) but well before T. cruzi entered in contact with humans in South America.

      Related collections

      Most cited references 96

      • Record: found
      • Abstract: found
      • Article: not found

      CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.

      The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. These modifications are incorporated into a new program, CLUSTAL W which is freely available.
        Bookmark
        • Record: found
        • Abstract: found
        • Article: not found

        MrBayes 3: Bayesian phylogenetic inference under mixed models.

        MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          BEAST: Bayesian evolutionary analysis by sampling trees

          Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at under the GNU LGPL license. Conclusion BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
            Bookmark

            Author and article information

            Affiliations
            Department of Biology, University of Maryland, College Park, Maryland, United States of America
            SBRI, United States America
            Author notes

            Conceived and designed the experiments: CAM. Performed the experiments: CF-L. Analyzed the data: CF-L CAM. Contributed reagents/materials/analysis tools: CAM. Wrote the paper: CF-L CAM.

            Contributors
            Role: Editor
            Journal
            PLoS Negl Trop Dis
            plos
            plosntds
            PLoS Neglected Tropical Diseases
            Public Library of Science (San Francisco, USA )
            1935-2727
            1935-2735
            August 2011
            2 August 2011
            : 5
            : 8
            3149036
            21829751
            PNTD-D-10-00294
            10.1371/journal.pntd.0001272
            (Editor)
            Flores-López, Machado. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
            Counts
            Pages: 13
            Categories
            Research Article
            Biology
            Evolutionary Biology
            Evolutionary Processes
            Genetics

            Infectious disease & Microbiology

            Comments

            Comment on this article