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Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing

BACKGROUND: Plasmodium vivax poses a significant challenge to malaria elimination due to its ability to cause relapsed infections from reactivation of dormant liver parasites called hypnozoites. We analyzed 69 P. vivax whole genome sequences obtained from subjects residing in three different village...

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Autores principales: Cowell, Annie N., Valdivia, Hugo O., Bishop, Danett K., Winzeler, Elizabeth A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6032790/
https://www.ncbi.nlm.nih.gov/pubmed/29973248
http://dx.doi.org/10.1186/s13073-018-0563-0
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author Cowell, Annie N.
Valdivia, Hugo O.
Bishop, Danett K.
Winzeler, Elizabeth A.
author_facet Cowell, Annie N.
Valdivia, Hugo O.
Bishop, Danett K.
Winzeler, Elizabeth A.
author_sort Cowell, Annie N.
collection PubMed
description BACKGROUND: Plasmodium vivax poses a significant challenge to malaria elimination due to its ability to cause relapsed infections from reactivation of dormant liver parasites called hypnozoites. We analyzed 69 P. vivax whole genome sequences obtained from subjects residing in three different villages along the Peruvian Amazon. This included 23 paired P. vivax samples from subjects who experienced recurrent P. vivax parasitemia following observed treatment with chloroquine and primaquine. METHODS: Genomic DNA was extracted from whole blood samples collected from subjects. P. vivax DNA was enriched using selective whole genome amplification and whole genome sequencing. We used single nucleotide polymorphisms (SNPs) from the core P. vivax genome to determine characteristics of the parasite population using discriminant analysis of principal components, maximum likelihood estimation of individual ancestries, and phylogenetic analysis. We estimated the relatedness of the paired samples by calculating the number of segregating sites and using a hidden Markov model approach to estimate identity by descent. RESULTS: We present a comprehensive dataset of population genetics of Plasmodium vivax in the Peruvian Amazonian. We define the parasite population structure in this region and demonstrate a novel method for distinguishing homologous relapses from reinfections or heterologous relapses with improved accuracy. The parasite population in this area was quite diverse with an estimated five subpopulations and evidence of a highly heterogeneous ancestry of some of the isolates, similar to previous analyses of P. vivax in this region. Pairwise comparison of recurrent infections determined that there were 12 homologous relapses and 3 likely heterologous relapses with highly related parasites. To the best of our knowledge, this is the first large-scale study to evaluate recurrent P. vivax infections using whole genome sequencing. CONCLUSIONS: Whole genome sequencing is a high-resolution tool that can identify P. vivax homologous relapses with increased sensitivity, while also providing data about drug resistance and parasite population genetics. This information is important for evaluating the efficacy of known and novel antirelapse medications in endemic areas and thus advancing the campaign to eliminate malaria. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-018-0563-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-60327902018-07-11 Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing Cowell, Annie N. Valdivia, Hugo O. Bishop, Danett K. Winzeler, Elizabeth A. Genome Med Research BACKGROUND: Plasmodium vivax poses a significant challenge to malaria elimination due to its ability to cause relapsed infections from reactivation of dormant liver parasites called hypnozoites. We analyzed 69 P. vivax whole genome sequences obtained from subjects residing in three different villages along the Peruvian Amazon. This included 23 paired P. vivax samples from subjects who experienced recurrent P. vivax parasitemia following observed treatment with chloroquine and primaquine. METHODS: Genomic DNA was extracted from whole blood samples collected from subjects. P. vivax DNA was enriched using selective whole genome amplification and whole genome sequencing. We used single nucleotide polymorphisms (SNPs) from the core P. vivax genome to determine characteristics of the parasite population using discriminant analysis of principal components, maximum likelihood estimation of individual ancestries, and phylogenetic analysis. We estimated the relatedness of the paired samples by calculating the number of segregating sites and using a hidden Markov model approach to estimate identity by descent. RESULTS: We present a comprehensive dataset of population genetics of Plasmodium vivax in the Peruvian Amazonian. We define the parasite population structure in this region and demonstrate a novel method for distinguishing homologous relapses from reinfections or heterologous relapses with improved accuracy. The parasite population in this area was quite diverse with an estimated five subpopulations and evidence of a highly heterogeneous ancestry of some of the isolates, similar to previous analyses of P. vivax in this region. Pairwise comparison of recurrent infections determined that there were 12 homologous relapses and 3 likely heterologous relapses with highly related parasites. To the best of our knowledge, this is the first large-scale study to evaluate recurrent P. vivax infections using whole genome sequencing. CONCLUSIONS: Whole genome sequencing is a high-resolution tool that can identify P. vivax homologous relapses with increased sensitivity, while also providing data about drug resistance and parasite population genetics. This information is important for evaluating the efficacy of known and novel antirelapse medications in endemic areas and thus advancing the campaign to eliminate malaria. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-018-0563-0) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-04 /pmc/articles/PMC6032790/ /pubmed/29973248 http://dx.doi.org/10.1186/s13073-018-0563-0 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Cowell, Annie N.
Valdivia, Hugo O.
Bishop, Danett K.
Winzeler, Elizabeth A.
Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
title Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
title_full Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
title_fullStr Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
title_full_unstemmed Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
title_short Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
title_sort exploration of plasmodium vivax transmission dynamics and recurrent infections in the peruvian amazon using whole genome sequencing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6032790/
https://www.ncbi.nlm.nih.gov/pubmed/29973248
http://dx.doi.org/10.1186/s13073-018-0563-0
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