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Single-cell genomics for dissection of complex malaria infections

Most malaria infections contain complex mixtures of distinct parasite lineages. These multiple-genotype infections (MGIs) impact virulence evolution, drug resistance, intra-host dynamics, and recombination, but are poorly understood. To address this we have developed a single-cell genomics approach...

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Autores principales: Nair, Shalini, Nkhoma, Standwell C., Serre, David, Zimmerman, Peter A., Gorena, Karla, Daniel, Benjamin J., Nosten, François, Anderson, Timothy J.C., Cheeseman, Ian H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032849/
https://www.ncbi.nlm.nih.gov/pubmed/24812326
http://dx.doi.org/10.1101/gr.168286.113
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author Nair, Shalini
Nkhoma, Standwell C.
Serre, David
Zimmerman, Peter A.
Gorena, Karla
Daniel, Benjamin J.
Nosten, François
Anderson, Timothy J.C.
Cheeseman, Ian H.
author_facet Nair, Shalini
Nkhoma, Standwell C.
Serre, David
Zimmerman, Peter A.
Gorena, Karla
Daniel, Benjamin J.
Nosten, François
Anderson, Timothy J.C.
Cheeseman, Ian H.
author_sort Nair, Shalini
collection PubMed
description Most malaria infections contain complex mixtures of distinct parasite lineages. These multiple-genotype infections (MGIs) impact virulence evolution, drug resistance, intra-host dynamics, and recombination, but are poorly understood. To address this we have developed a single-cell genomics approach to dissect MGIs. By combining cell sorting and whole-genome amplification (WGA), we are able to generate high-quality material from parasite-infected red blood cells (RBCs) for genotyping and next-generation sequencing. We optimized our approach through analysis of >260 single-cell assays. To quantify accuracy, we decomposed mixtures of known parasite genotypes and obtained highly accurate (>99%) single-cell genotypes. We applied this validated approach directly to infections of two major malaria species, Plasmodium falciparum, for which long term culture is possible, and Plasmodium vivax, for which no long-term culture is feasible. We demonstrate that our single-cell genomics approach can be used to generate parasite genome sequences directly from patient blood in order to unravel the complexity of P. vivax and P. falciparum infections. These methods open the door for large-scale analysis of within-host variation of malaria infections, and reveal information on relatedness and drug resistance haplotypes that is inaccessible through conventional sequencing of infections.
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spelling pubmed-40328492014-12-01 Single-cell genomics for dissection of complex malaria infections Nair, Shalini Nkhoma, Standwell C. Serre, David Zimmerman, Peter A. Gorena, Karla Daniel, Benjamin J. Nosten, François Anderson, Timothy J.C. Cheeseman, Ian H. Genome Res Method Most malaria infections contain complex mixtures of distinct parasite lineages. These multiple-genotype infections (MGIs) impact virulence evolution, drug resistance, intra-host dynamics, and recombination, but are poorly understood. To address this we have developed a single-cell genomics approach to dissect MGIs. By combining cell sorting and whole-genome amplification (WGA), we are able to generate high-quality material from parasite-infected red blood cells (RBCs) for genotyping and next-generation sequencing. We optimized our approach through analysis of >260 single-cell assays. To quantify accuracy, we decomposed mixtures of known parasite genotypes and obtained highly accurate (>99%) single-cell genotypes. We applied this validated approach directly to infections of two major malaria species, Plasmodium falciparum, for which long term culture is possible, and Plasmodium vivax, for which no long-term culture is feasible. We demonstrate that our single-cell genomics approach can be used to generate parasite genome sequences directly from patient blood in order to unravel the complexity of P. vivax and P. falciparum infections. These methods open the door for large-scale analysis of within-host variation of malaria infections, and reveal information on relatedness and drug resistance haplotypes that is inaccessible through conventional sequencing of infections. Cold Spring Harbor Laboratory Press 2014-06 /pmc/articles/PMC4032849/ /pubmed/24812326 http://dx.doi.org/10.1101/gr.168286.113 Text en © 2014 Nair et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Method
Nair, Shalini
Nkhoma, Standwell C.
Serre, David
Zimmerman, Peter A.
Gorena, Karla
Daniel, Benjamin J.
Nosten, François
Anderson, Timothy J.C.
Cheeseman, Ian H.
Single-cell genomics for dissection of complex malaria infections
title Single-cell genomics for dissection of complex malaria infections
title_full Single-cell genomics for dissection of complex malaria infections
title_fullStr Single-cell genomics for dissection of complex malaria infections
title_full_unstemmed Single-cell genomics for dissection of complex malaria infections
title_short Single-cell genomics for dissection of complex malaria infections
title_sort single-cell genomics for dissection of complex malaria infections
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032849/
https://www.ncbi.nlm.nih.gov/pubmed/24812326
http://dx.doi.org/10.1101/gr.168286.113
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