Experimental evolution, genetic analysis and genome re-sequencing reveal the mutation conferring artemisinin resistance in an isogenic lineage of malaria parasites

BMC Genomics

Research Article

Laurence Loewe¹  Pedro Cravo²  Louise Rodrigues²  Sofia Borges³  Dario Beraldi⁴  Mark Blaxter⁵  Richard Fawcett⁶  Katarzyna Modrzynska⁶  Alison Creasey⁶  Paul Hunt⁷  Axel Martinelli⁸  Thomas D Otto⁹  Arnab Pain^1,10  Sujai Kumar^1,11  Marian Thomson^1,11  Urmi Trivedi^1,11 

[1] Centre for Systems Biology at Edinburgh, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Centro de Malaria e Outras Doenças Tropicais/IHMT/UEI Biologia Molecular, Universidade Nova de Lisboa, Lisbon, Portugal;Centro de Malaria e Outras Doenças Tropicais/IHMT/UEI Malaria, Universidade Nova de Lisboa, Lisbon, Portugal;Institute for Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Roslin, UK;Institute for Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;The GenePool, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Institute for Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Institute for Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Centre for Immunity, Infection and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Institute for Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;Centro de Malaria e Outras Doenças Tropicais/IHMT/UEI Biologia Molecular, Universidade Nova de Lisboa, Lisbon, Portugal;Pathogen Genomics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK;Pathogen Genomics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK;Computational Bioscience Research Center, Chemical and Life Sciences and Engineering Division, King Abdullah University of Science and Technology, 23955-6900, Thuwal, Kingdom of Saudi Arabia;The GenePool, School of Biological Sciences, University of Edinburgh, Edinburgh, UK;

关键词: Chloroquine;    Artemisinin;    Artesunate;    Pyrimethamine;    Read Coverage;   

DOI  :  10.1186/1471-2164-11-499

 received in 2010-03-10, accepted in 2010-09-16,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundClassical and quantitative linkage analyses of genetic crosses have traditionally been used to map genes of interest, such as those conferring chloroquine or quinine resistance in malaria parasites. Next-generation sequencing technologies now present the possibility of determining genome-wide genetic variation at single base-pair resolution. Here, we combine in vivo experimental evolution, a rapid genetic strategy and whole genome re-sequencing to identify the precise genetic basis of artemisinin resistance in a lineage of the rodent malaria parasite, Plasmodium chabaudi. Such genetic markers will further the investigation of resistance and its control in natural infections of the human malaria, P. falciparum.ResultsA lineage of isogenic in vivo drug-selected mutant P. chabaudi parasites was investigated. By measuring the artemisinin responses of these clones, the appearance of an in vivo artemisinin resistance phenotype within the lineage was defined. The underlying genetic locus was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (Illumina® Solexa) defined the point mutations, insertions, deletions and copy-number variations arising in the lineage. Eight point mutations arise within the mutant lineage, only one of which appears on chromosome 2. This missense mutation arises contemporaneously with artemisinin resistance and maps to a gene encoding a de-ubiquitinating enzyme.ConclusionsThis integrated approach facilitates the rapid identification of mutations conferring selectable phenotypes, without prior knowledge of biological and molecular mechanisms. For malaria, this model can identify candidate genes before resistant parasites are commonly observed in natural human malaria populations.

【 授权许可】

CC BY   
© Hunt et al; licensee BioMed Central Ltd. 2010