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Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum

BACKGROUND: Simultaneous infection with multiple malaria parasite strains is common in high transmission areas. Quantifying the number of strains per host, or the multiplicity of infection (MOI), provides additional parasite indices for assessing transmission levels but it is challenging to measure...

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Autores principales: Mitchell, Rebecca M., Zhou, Zhiyong, Sheth, Mili, Sergent, Sheila, Frace, Michael, Nayak, Vishal, Hu, Bin, Gimnig, John, ter Kuile, Feiko, Lindblade, Kim, Slutsker, Laurence, Hamel, Mary J., Desai, Meghna, Otieno, Kephas, Kariuki, Simon, Vigfusson, Ymir, Shi, Ya Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885407/
https://www.ncbi.nlm.nih.gov/pubmed/33593329
http://dx.doi.org/10.1186/s12936-021-03624-2
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author Mitchell, Rebecca M.
Zhou, Zhiyong
Sheth, Mili
Sergent, Sheila
Frace, Michael
Nayak, Vishal
Hu, Bin
Gimnig, John
ter Kuile, Feiko
Lindblade, Kim
Slutsker, Laurence
Hamel, Mary J.
Desai, Meghna
Otieno, Kephas
Kariuki, Simon
Vigfusson, Ymir
Shi, Ya Ping
author_facet Mitchell, Rebecca M.
Zhou, Zhiyong
Sheth, Mili
Sergent, Sheila
Frace, Michael
Nayak, Vishal
Hu, Bin
Gimnig, John
ter Kuile, Feiko
Lindblade, Kim
Slutsker, Laurence
Hamel, Mary J.
Desai, Meghna
Otieno, Kephas
Kariuki, Simon
Vigfusson, Ymir
Shi, Ya Ping
author_sort Mitchell, Rebecca M.
collection PubMed
description BACKGROUND: Simultaneous infection with multiple malaria parasite strains is common in high transmission areas. Quantifying the number of strains per host, or the multiplicity of infection (MOI), provides additional parasite indices for assessing transmission levels but it is challenging to measure accurately with current tools. This paper presents new laboratory and analytical methods for estimating the MOI of Plasmodium falciparum. METHODS: Based on 24 single nucleotide polymorphisms (SNPs) previously identified as stable, unlinked targets across 12 of the 14 chromosomes within P. falciparum genome, three multiplex PCRs of short target regions and subsequent next generation sequencing (NGS) of the amplicons were developed. A bioinformatics pipeline including B4Screening pathway removed spurious amplicons to ensure consistent frequency calls at each SNP location, compiled amplicons by SNP site diversity, and performed algorithmic haplotype and strain reconstruction. The pipeline was validated by 108 samples generated from cultured-laboratory strain mixtures in different proportions and concentrations, with and without pre-amplification, and using whole blood and dried blood spots (DBS). The pipeline was applied to 273 smear-positive samples from surveys conducted in western Kenya, then providing results into StrainRecon Thresholding for Infection Multiplicity (STIM), a novel MOI estimator. RESULTS: The 24 barcode SNPs were successfully identified uniformly across the 12 chromosomes of P. falciparum in a sample using the pipeline. Pre-amplification and parasite concentration, while non-linearly associated with SNP read depth, did not influence the SNP frequency calls. Based on consistent SNP frequency calls at targeted locations, the algorithmic strain reconstruction for each laboratory-mixed sample had 98.5% accuracy in dominant strains. STIM detected up to 5 strains in field samples from western Kenya and showed declining MOI over time (q < 0.02), from 4.32 strains per infected person in 1996 to 4.01, 3.56 and 3.35 in 2001, 2007 and 2012, and a reduction in the proportion of samples with 5 strains from 57% in 1996 to 18% in 2012. CONCLUSION: The combined approach of new multiplex PCRs and NGS, the unique bioinformatics pipeline and STIM could identify 24 barcode SNPs of P. falciparum correctly and consistently. The methodology could be applied to field samples to reliably measure temporal changes in MOI.
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spelling pubmed-78854072021-02-17 Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum Mitchell, Rebecca M. Zhou, Zhiyong Sheth, Mili Sergent, Sheila Frace, Michael Nayak, Vishal Hu, Bin Gimnig, John ter Kuile, Feiko Lindblade, Kim Slutsker, Laurence Hamel, Mary J. Desai, Meghna Otieno, Kephas Kariuki, Simon Vigfusson, Ymir Shi, Ya Ping Malar J Research BACKGROUND: Simultaneous infection with multiple malaria parasite strains is common in high transmission areas. Quantifying the number of strains per host, or the multiplicity of infection (MOI), provides additional parasite indices for assessing transmission levels but it is challenging to measure accurately with current tools. This paper presents new laboratory and analytical methods for estimating the MOI of Plasmodium falciparum. METHODS: Based on 24 single nucleotide polymorphisms (SNPs) previously identified as stable, unlinked targets across 12 of the 14 chromosomes within P. falciparum genome, three multiplex PCRs of short target regions and subsequent next generation sequencing (NGS) of the amplicons were developed. A bioinformatics pipeline including B4Screening pathway removed spurious amplicons to ensure consistent frequency calls at each SNP location, compiled amplicons by SNP site diversity, and performed algorithmic haplotype and strain reconstruction. The pipeline was validated by 108 samples generated from cultured-laboratory strain mixtures in different proportions and concentrations, with and without pre-amplification, and using whole blood and dried blood spots (DBS). The pipeline was applied to 273 smear-positive samples from surveys conducted in western Kenya, then providing results into StrainRecon Thresholding for Infection Multiplicity (STIM), a novel MOI estimator. RESULTS: The 24 barcode SNPs were successfully identified uniformly across the 12 chromosomes of P. falciparum in a sample using the pipeline. Pre-amplification and parasite concentration, while non-linearly associated with SNP read depth, did not influence the SNP frequency calls. Based on consistent SNP frequency calls at targeted locations, the algorithmic strain reconstruction for each laboratory-mixed sample had 98.5% accuracy in dominant strains. STIM detected up to 5 strains in field samples from western Kenya and showed declining MOI over time (q < 0.02), from 4.32 strains per infected person in 1996 to 4.01, 3.56 and 3.35 in 2001, 2007 and 2012, and a reduction in the proportion of samples with 5 strains from 57% in 1996 to 18% in 2012. CONCLUSION: The combined approach of new multiplex PCRs and NGS, the unique bioinformatics pipeline and STIM could identify 24 barcode SNPs of P. falciparum correctly and consistently. The methodology could be applied to field samples to reliably measure temporal changes in MOI. BioMed Central 2021-02-16 /pmc/articles/PMC7885407/ /pubmed/33593329 http://dx.doi.org/10.1186/s12936-021-03624-2 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research
Mitchell, Rebecca M.
Zhou, Zhiyong
Sheth, Mili
Sergent, Sheila
Frace, Michael
Nayak, Vishal
Hu, Bin
Gimnig, John
ter Kuile, Feiko
Lindblade, Kim
Slutsker, Laurence
Hamel, Mary J.
Desai, Meghna
Otieno, Kephas
Kariuki, Simon
Vigfusson, Ymir
Shi, Ya Ping
Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum
title Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum
title_full Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum
title_fullStr Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum
title_full_unstemmed Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum
title_short Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum
title_sort development of a new barcode-based, multiplex-pcr, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of plasmodium falciparum
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885407/
https://www.ncbi.nlm.nih.gov/pubmed/33593329
http://dx.doi.org/10.1186/s12936-021-03624-2
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