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      estMOI: estimating multiplicity of infection using parasite deep sequencing data

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          Abstract

          Summary: Individuals living in endemic areas generally harbour multiple parasite strains. Multiplicity of infection (MOI) can be an indicator of immune status and transmission intensity. It has a potentially confounding effect on a number of population genetic analyses, which often assume isolates are clonal. Polymerase chain reaction-based approaches to estimate MOI can lack sensitivity. For example, in the human malaria parasite Plasmodium falciparum, genotyping of the merozoite surface protein ( MSP1/2) genes is a standard method for assessing MOI, despite the apparent problem of underestimation. The availability of deep coverage data from massively parallizable sequencing technologies means that MOI can be detected genome wide by considering the abundance of heterozygous genotypes. Here, we present a method to estimate MOI, which considers unique combinations of polymorphisms from sequence reads. The method is implemented within the estMOI software. When applied to clinical P.falciparum isolates from three continents, we find that multiple infections are common, especially in regions with high transmission.

          Availability and implementation: estMOI is freely available from http://pathogenseq.lshtm.ac.uk.

          Contact: samuel.assefa@ 123456lshtm.ac.uk

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references11

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          Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

          Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. 1,2 Here we describe methods for large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short term culture. Analysis of 86,158 exonic SNPs that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome.
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            Close kinship within multiple-genotype malaria parasite infections

            Malaria infections containing multiple parasite genotypes are ubiquitous in nature, and play a central role in models of recombination, intra-host dynamics, virulence, sex ratio, immunity and drug resistance evolution in Plasmodium. While these multiple infections (MIs) are often assumed to result from superinfection (bites from multiple infected mosquitoes), we know remarkably little about their composition or generation. We isolated 336 parasite clones from eight patients from Malawi (high transmission) and six from Thailand (low transmission) by dilution cloning. These were genotyped using 384 single-nucleotide polymorphisms, revealing 22 independent haplotypes in Malawi (2–6 per MI) and 15 in Thailand (2–5 per MI). Surprisingly, all six patients from Thailand and six of eight from Malawi contained related haplotypes, and haplotypes were more similar within- than between-infections. These results argue against a simple superinfection model. Instead, the observed kinship patterns may be explained by inoculation of multiple related haploid sporozoites from single mosquito bites, by immune suppression of parasite subpopulations within infections, and serial transmission of related parasites between people. That relatedness is maintained in endemic areas in the face of repeated bites from infected mosquitoes has profound implications for understanding malaria transmission, immunity and intra-host dynamics of co-infecting parasite genotypes.
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              Age-dependent carriage of multiple Plasmodium falciparum merozoite surface antigen-2 alleles in asymptomatic malaria infections.

              Genetic diversity of the merozoite surface antigen-2 gene of the human malaria parasite Plasmodium falciparum has been analyzed in a Senegalese village where malaria is holoendemic. A cross-sectional survey of 65 residents was performed in 1992 during the high transmission season. Plasmodium falciparum was detected both by microscopy (77% positive samples) and DNA amplification using a single (29% or 38% positive samples, depending on the primers used) or nested polymerase chain reaction (PCR) (78% positive samples). The overlap between the positive nested PCR and microscopic examination was not complete. The PCR fragments were analyzed for size polymorphism on agarose gels, and were subsequently assigned to the major allelic families 3D7 or FC27 by hybridization with family-specific probes. Both allelic families were found, with a slightly higher prevalence for FC27. Chimeric alleles that failed to hybridize under stringent conditions to the reference probes were also observed. Some were typed using a novel PCR approach, using hybrid pairs of primers, consisting of a family-specific sense oligonucleotide combined with an antisense oligonucleotide specific for the other family. Combining typing techniques, 82% of the positive PCR results yielded more than one band. Both the overall number of fragments and the number of allelic types per carrier were markedly reduced around the age of 15 years. The number of DNA fragments decreased abruptly from an average of four per carrier before the age of 15 years to an average of two in individuals more than 15 years of age.(ABSTRACT TRUNCATED AT 250 WORDS)
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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                1 May 2014
                17 January 2014
                17 January 2014
                : 30
                : 9
                : 1292-1294
                Affiliations
                1London School of Hygiene and Tropical Medicine, WC1E 7HT, London, UK, 2Wellcome Trust Sanger Institute, CB10 1SA, Hinxton, UK and 3Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Box 30096 BT3, Blantyre, Malawia
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Martin Bishop

                Article
                btu005
                10.1093/bioinformatics/btu005
                3998131
                24443379
                19b6e91f-b1e5-4029-8449-b968896b4e60
                © The Author 2013. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 November 2013
                : 12 December 2013
                : 30 December 2013
                Page count
                Pages: 3
                Categories
                Applications Notes
                Genome Analysis

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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