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Detection of low-density Plasmodium falciparum infections using amplicon deep sequencing

Angela M. Early, Rachel F. Daniels, Timothy M. Farrell, Jonna Grimsby, Sarah K. Volkman, Dyann F. Wirth, Bronwyn L. MacInnis, Daniel E. Neafsey
doi: https://doi.org/10.1101/453472
Angela M. Early
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
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  • For correspondence: early@broadinstitute.org
Rachel F. Daniels
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
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Timothy M. Farrell
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
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Jonna Grimsby
3Genomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
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Sarah K. Volkman
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
4Simmons University, College of Natural, Behavioral, and Health Sciences, Boston, MA, 02115 USA
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Dyann F. Wirth
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
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Bronwyn L. MacInnis
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
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Daniel E. Neafsey
1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115 USA
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Abstract

Background Deep sequencing of targeted genomic regions is becoming a common tool for understanding the dynamics and complexity of Plasmodium infections, but its lower limit of detection is currently unknown. Here, a new amplicon analysis tool, the Parallel Amplicon Sequencing Error Correction (PASEC) pipeline, is used to evaluate the performance of amplicon sequencing on low-density Plasmodium DNA samples. Illumina-based sequencing of two P. falciparum genomic regions (CSP and SERA2) was performed on two types of samples: in vitro DNA mixtures mimicking low-density infections (1-200 genomes/μl) and extracted blood spots from a combination of symptomatic and asymptomatic individuals (44-653,080 parasites/μl). Three additional analysis tools—DADA2, HaplotypR, and SeekDeep—were applied to both datasets and the precision and sensitivity of each tool were evaluated.

Results Amplicon sequencing can contend with low-density samples, showing reasonable detection accuracy down to a concentration of 5 Plasmodium genomes/μl. Due to increased stochasticity and background noise, however, all four tools showed reduced sensitivity and precision on samples with very low parasitemia (<5 copies/μl) or low read count (<100 reads per amplicon). PASEC could distinguish major from minor haplotypes with an accuracy of 90% in samples with at least 30 Plasmodium genomes/μl, but only 61% at low Plasmodium concentrations (<5 genomes/μl) and 46% at very low read counts (<25 reads per amplicon). The four tools were additionally used on a panel of extracted parasite-positive blood spots from natural malaria infections. While all four identified concordant patterns of complexity of infection (COI) across four sub-Saharan African countries, the COI values obtained for individual samples differed in some cases.

Conclusions Amplicon deep sequencing can be used to determine the complexity and diversity of low-density Plasmodium infections. Despite differences in their approach, four state-of-the-art tools resolved known haplotype mixtures with similar sensitivity and precision. Researchers can therefore choose from multiple robust approaches for analyzing amplicon data, however, error filtration approaches should not be uniformly applied across samples of varying parasitemia. Samples with very low parasitemia and very low read count have higher false positive rates and call for read count thresholds that are higher than current recommendations.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted February 19, 2019.
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Detection of low-density Plasmodium falciparum infections using amplicon deep sequencing
Angela M. Early, Rachel F. Daniels, Timothy M. Farrell, Jonna Grimsby, Sarah K. Volkman, Dyann F. Wirth, Bronwyn L. MacInnis, Daniel E. Neafsey
bioRxiv 453472; doi: https://doi.org/10.1101/453472
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Detection of low-density Plasmodium falciparum infections using amplicon deep sequencing
Angela M. Early, Rachel F. Daniels, Timothy M. Farrell, Jonna Grimsby, Sarah K. Volkman, Dyann F. Wirth, Bronwyn L. MacInnis, Daniel E. Neafsey
bioRxiv 453472; doi: https://doi.org/10.1101/453472

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